heavy truck splash and spray testing: phase iitested. these devices consisted of flexible fiber...
TRANSCRIPT
1. Report No.
4. Title and Subtitle
2. Government Accession No. )
Heavy Truck Splash and Spray Testing: Phase II
Technical Report Documentation Page
3. Recipient's Cotolog No.
S. Report Oote
August 1985 6. Performing Organization Code
~~~~~~~~~~~~~~~~~~~~~~~~~~8. P~~rmingO~~izoHon ReportNo. 7· Author's> Rodger J. Kappa, Olga Pendleton, Richard A.
Zimmer, Valmon Pezoldt, and Ronald Bremer 9. Performing Organization Nome and Address
Texas Transportatiot. Institute The Texas A&M University System College Station, Tex~s 77843
~~~--------~------~------~----~--------~--~ i 2. Sponsoring Agency Nome and Address
Motor Vehicle Manufacturers Association of the United States
300 New Center Bldg. n,;atrnit Mirhioan 4M~~
1 S. Supplementary Notes
16. Abstract
RF7040 Final 10. Worlc Unit No. (TRAIS)
J 1. Contract or Grant No.
RF7040 13. Type of Report ond Period Covered
Final March-August 1985
14. Sponsoring Agency Code
TTI 85M-C5138
Five different combinations of splash and spray reduction devices on four different tractors and three different trailers-van, tanker, and flat-bed were tested. These devices consisted of flexible fiber skirting, spray flaps made up of "astroturf11 on a flat plastic backing, and also of dynamic fairings mounted on cab roo1·s. The location of skirts was co-varied with use of the aerodynamic fairing, and spray production compared against a baseline condition in which only plain mudflaps were mounted on the rearmost axle of the vehicle combination. Two of these five conditions were the same as the Department of Transportation's proposed short-term (1 year) a.nd long-term (4 year) spray control configurations.
Spray cloud densities were measured by laser transmissometers and documented by videotape taken both from a stationary camera and from a chase car. Observers in the chase car made subjective judgements of vis i bi 1 i ty through the truck spray
1 and made measurements of the.spray usin~ an.on-board laser transm~ssome~er: Results from at least s1xteen repl1cat1ons of each test cond1t1on 1nd1cate
a complex relationship among treatments, vehicle types, and wind. The presence or absence of an aerodynamic fairing on some tractor designs is a crucial factor, but on others has little effect. The efficacy of treatments studied in this research is much less for tank and flatbed trailers than for van trailers.
17, Key Nards l 18. Oi stribution Statement
I I I I !
19. Seeur• ty .:loss; f. ~ ~r ~he 5 reoortl 20. Seeuri ty Cl as sd. ! of !i·u 5 page1
UNCL. UNCL. Form DOT F 1700.7 s-72) Reproduction of com pi eted poge authorized
ACKNOWLEDGEMENTS
This project could not h~ve been completed without the assistance
and care of many people in many different organizations. The authors
would especially like to thank our Motor Vehicle Manufactu.rers
Association (MVMA) Project Manager, Carl McConnell, for his patience and
unfailing good humor in piloting us "one more time." Special thanks also
are due to the members of the Splash and Spray Task Force: Ron Joyner,
General Motors, Clark Gorte, Ford Motor Co., and Kjell Pedersen,
International Harvester.
were:
The organizations that provided test vehicles and much assistance
International Harvester Corporation
Leaseway Transportation, Incorporated
Gelco Truck Leasing Company
Central Freight Lines
Heil Corporation
Hobbs Trailer Company
Test Equipment was furnished with much "one-on-one" technical
support by:
Monsanto Company
Schlegel Corporation
iii
The ITI Test Team at the Bryan Research and Extension Cente: which
once again translated the authors' plans into reality was comprised of
Don Cangalose and his test pad crew consisting of drivers Ken Hazlewood,
Leon Wade, Bob O'Connell, and general support personnel Scott
Oobrovolny, Gary Watters, James Dublin, and Lance Bullard. Operation of
the ground station and much preparatory electronic instrumentation were
again handled by John Curik, with test pad electronic support from John
Ragsdale. Chase car operations were headed by John Holmgreen, with
Katherine Palko and Sheldon Wolstein. Juanita Brumbaugh handled
communications and coordination with much good cheer. James Bradley
handled the video documentation.
A special note of thanks to Mr. Charles Brenton of the
University's Meteorology Department who kept us informed of the future
vagaries of the fickle "prevailing" winds during testing.
This report was produced with the editorial coordination of Ruth
Ellen Fleming and the word processing skills of Teresa Tenorio and
Martha Kacer.
iv
TABLE OF CONTENTS
PAGE
EXECUTIVE SUMMARY ••••••••••••••••••••••••••••••••••••••••••••••••• E-1
1.0 INTRODUCTION AND BACKGROUN0 •••••••••••••••••••••••••••••••••• 1-1 1.,1 Introduction •••••••••••••••••••••••••••••••••••••••••••• 1-1 1.2 Background •••••••••••••••••••••••••••••••••••••••••••••• 1-2 1.3 ObJectivas •••••••••••••••••••••••••••••••••••••••••••••• 1-4
2.0
3.0
TEST 2.1 2.2
TEST 3.1 3.2
3.3
PREPARATION ••••••••••••••••••••••••••••••••••••••••••••• 2-1 Layout & Test Surfaces .................................. 2-1 Instrumentation •••••••••••••••••••••• -••••••••••••••••••• 2-5 2.2.1 Video Coverage •••••••••••••••••••••••••••••••••••• 2-5 2.2.2 Laser Transmissometers •••••••••••••••••••••••••••• 2-5 2.2.3 Base Station Data Processing and
Reduction ••••••••••••••••••••••••••••••••••••••••• 2-11 2.2.4 Chase Car Instrumentation ••••••••••••••••••••••••• 2-17 2.2.5 Other Test Section Instrumentation •••••••••••••••• 2-25
PLA'N ••••••••••••••••••••••••••••••••• ~ •••••••••••••••••• 3-1 Test Conditions Matrix and Run Record ••••••••••••••••••• 3-1 Test Vehic:les and Eguipment ••••••••••••••••••••••••••••• 3-6 3.2.1 Splash and Spray Control Equipment •••••••••••••••• l-6 3.2.2 Study A Vehicles .................................... 3-7 3.2.3 Study B Vehicles •••••••••••••••••••••••••••••••••• 3·7 3.,2.4 Study c Vehicles •••••••••••••••••••••••••••••••••• J-7 3.2 .5 S.peci a 1 Studies ••••••••••••••••••••••••••••••••••• 3-15 Test Run Procedu.res ••••••••••••••••••••••••••••••••••••• 3-21 3.3.1 Grourid Rules •••••••••••••••••••••••••••••••••••••• 3-21 3.3.2 Test Section Procedures ••••••••••••••••••••••••••• J-22 3.3.3 Chase Car Procedures •••••••••••••••••••••••••••••• 3·24
4.0 STATISTICAL METHODS AND RESULTS •••••••••••••••••••••••••••••• 4-1 4.1 Statistical Methods ••••••••••••••••••••••••••••••••••••• 4-1
4.1.1 Study A ••••••••••••••••••••••••••••••••••••••••••• 4-1 4.1.2 Study 8 ••••••••••••••••••••••••••••••••••••••••••• 4-12 4.1.3 Study C ••••••••••••••••••••••••••••••• ~ ••••••••••• 4-13
4.2 Results •••••••••••••••••••••••••••••••• , ••••••••••••••••• 4-15 4.2.1 Study A••••••••••••••••••••••••••••••••••••••••••·4-15 4.2 .2 Stu·dy B ••••••••••••••••••••••••••••••••••••••••••• 4-27 4.2.3 Study C ••••••••••••••••••••••••••••••••••••••••••• 4-35 4.2.4 Surnrnary ••••••••••••••••••••••••••••••••••••••••••• 4-40
4.3 Chase Car Results ••••••••••••••••••••••••••••••••••••••• 4-43 4.4 Correlation Between Sensors ••••••••••••••••••••••••••••• 4-52 4.5 Results of Special Studies •••••••••••••••••••••••••••••• 4-52 4.6 Initial Splash Phenomenon ••••••••••••••••••••••••••••••• 4-57
5.0 SUMMARY OF FINDINGS AND RECOMMENDATIONS •••••••••••••••••••••• S-1 5.1 Summary of Findinss ••••••••••••••••••••••••••••••••••••• S-1
5.1.1 Answers to Fundamental Questions •••••••••••••••••• S-1 5.1.2 Study B Findings ••••••••••••• _ •••••••••••••••••••• S-5 5.1.3 Study C Findings •••••••••••••••••••••••••••••••••• 5-5
v
TOC ~contd.)
5.1.4 Chase Car Findings •••••••••••••••••••••••••••••••• 5-6 5.1.5 Other _Study Findings •••••••••••••••••••••••••••••• S-7
5.2 Recommendations ••••••••••••••••••••••••••••••••••••••••• S-7 REFERENCES ••••••••••••••••••••••••••••••••••••••••••••••••••• 5-10
APPENDIX,A- Compilation of All Runs •••••••••••••••••••••••••••••• A-1
APPENDIX B Test Vehicle Data •••••••••••••••••••••••••••••••••••• B-1
APPENDIX C Equipment Installation Instructions and Installed Measurements •••••••••••••••••••••••••• C-1
vi
EXECUTIVE SUMMARY
Introduction
EXECUTIVE SUMMARY
HEAVY TRUCK SPLASH AND SPRAY TESTING
PHASE II
This report documents a six-month intensive test progra .. l in which
a number of different tractor-trailer combinations were equip~ed with
state-of-the-art splash and spray reduction devices and those treatments
evaluated. This program was sponsored by the Motor Vehicle Manufacturers
Association ( MVMA) of the United States, Inc. In a test program ( 1) that
was a predecessor to that reported here, approaches which had been
deve 1 oped over the past 10 to 15 years for measurtng spray c 1 ouds fr.om
heavy vehicles under simulated field conditions were refined. For both
these simulations, test vehicles crossed a water-flooded test pad to
produce a cloud of spray which was both photographed, and measured by
~eans of laser transmissometers. This report documents the results of a
second test program.
In both of these test efforts, spray reduction devices consisted
of treated back flaps, side mounted valances and aerodynamic fairings on
the tops of the tractors.
Background
Splash and spray clouds raised by heavy trucks have long been a
source of irritation to motorists. Although there is little or no
documented proof that this source of irritation has led to accidents or
fatalities, such circumstances are easily conceivable.
E-3
Since the late 1960 1 s or earlier, groups such as the Western
Highway Institute, MVMA, and others have tested proprietary designs and
generic ideas to reduce splash and spray. The National Highway Traffic
Safety Administration {NHTSA), early on, proposed rulemaking to reduce
the annoyance and possible dangers of splash and spray produced by heavy
commercial vehicles. Prior to rulemaking, NHTSA ran a limited number of
full-scale spray-reduction tests at the Transportation Research Center
of Ohio. ·
In January of 1984 NHTSA began a new series of tests at Ft.
Stockton, Texas with advanced instrumentation. These full-scale tests
were designed to achieve objective measurements and to correlate lab
testing ranking of various types of spray-suppression devices on various
vehicles with these full scale test results.
MVMA in the interim decided that supplementary tests at a test
site which duplicated the Ft. Stockton approach as closely as possible
would be useful in filling gaps in the NHTSA data. These tests would
ensure that the devices likely to be required by rulemaking would be
practicable, reliable, and effective.
In the period following the conclusion of the MVMA splash and
spray tests, the NHTSA did propose rulemaking. These rules, among other
things, mandated retrofit and equipping of new vehicles with skirts and
flaps with rated performance characteristics as measured by a prescribed
.. tunnel .. test setup. One year after adoption of the regulations, heavy
commercial vehicles would have to be equipped with spray suppressant
flaps on all axles, and skirts on the rear axle. Four years after the
regulations took effect, skirts would be required on ill axles. Aeroai ds
or other aerodynamic treatments were not mentioned.
E-4
MVMA'~ Splash and Spray Task Force then decided to fund further
studies. In these studies the top five vehicle treatment configurations,
plus the NHTSA proposed treatments, would be subjected to rigorous
testing, with sufficient trials of each configuration to assure that
adequate statistical analysis of the data could be done.
ObJectives
The 198;;) test project had the following specific objectives:
1. To supplement data already available and to analyze the
aggregate data set to provide a basis for reasonable and effective
actions for addressing the problem of splash/spray reduction from
tractor-trailer combination vehicles;
2. To obtain sufficient test runs on each vehicle treatment
configuration to assure adequate statistical anal.ysis of the data, and
both valid and reliable conclus_ions;
3. To obtain test data on the effects of treatments on trailers
other than van-trailers, but mandated for treatment by NHTSA;
4. To investigate methods by whi~h reliable spray measurement data
can be obtained under highway conditions.
E-5
Layout and Test Surfaces
Figure E-1 provides a general plan of the test section through
which the splash and spray control equipped vehicles passed on every
run. The asphaltic concrete test pad surface used in the Phase 1 tests
last year was once again used, but was supplemented by a strip of
Jennite (coal tar) coating which was laid down on top of the original
portland cement aggregate surface of the "'irbase apron. The
supplementary surface measured 12 x 660 ft, and was located south of the
original (and primary) test surface. The water supply was adjusted to
provide the proper surface water depth on each pad throughout testing.
The nominal water depth maintained during all testing was 0.04 to 0.06
inch on the north (original) pad,- except during Study B, which studied
water depth differences. Local irregularities and the south-inclining
surface of the air base apron precluded uniform water depth maintenance
on the south test surface and it was left to be somewhat representative
of a "real worldn uncontrolled condition.
Four laser transmissometers were located in the south section and
four more lasers were located at the exact locations used in the 1984
tests on the north section. The two lasgr locations were situated
exac;t 1 y 500 feet apart.
No reference checkerboards were used in these tests, since
photography was not considered to be the ---u1aj or method of documentation.
A reference mark for the chase-car occupants to begin their
proc~dures was located just south of the jennite-coated surface, at the
spot designated "Passing Cone" in Figure E-1. A 1975 Buick, the target
vehicle used for chase car observers to make judgements of visibility,
was located 72 feet from the vehicle path to the west, and 1975 feet
E-6
rn I
........
•paaalng• Cone •
OIRfCTION. __... Ot TfiAV(L
Laae 1-4
JENNITE SURFACE
• • • • - . ~
ra~· !I
Loetectora 1-4
Water Line
Target Vehicle
ASPHALT .URFACE T 72'
• ~ ·}::±1 ..
ffivtdeo Houae Laaera~ Loetec &-8 a-a
Teat Trailer I I
L--1 L..t ·I •I •I •I •I ·I H •I ~ 11 4~0' 500' 660' 886' 800' 840' 810' 1876'
NORTH
Figure E-1 General layout of the Test Section
from the Passing Cone. A general view of the test section, taken from an
elevated position to the northeast, is provided in Figure E-2.
Instrumentation
The primary pictorial coverage on this project was videotape. Two
camera and recorder setups were used. One camera was situated uprange
from the north laser set, 250 feet distant and on the east side of the
vehicle path.
The other camera was located in the chase car, si~uated such that
it could record the view out the windshield of this vehicle as it
tracked the test vehicle at a distance of 100 feet.
Laser Transmissometers
Quantitative spray density data were measured by means of eight
low power lasers (5 mw) aimed, parallel to the vehicle path, at photo
detectors or light meters. To account for crosswind, two lasers were
located: symmetrically on each side of each test track at two locations.
The lasers were located 50 ft from the detectors as shown in Figure E-1.
The lateral and vertical placement is shown in Figure E-3.
Base Station Data Processing and Reduction
The signals from the detector were displayed on meters at the
detectors for alignment and then sent to the telemetry system in the
control trailer. The eight signals were transmitted via radio to a
permanent base station. At the base station the data were first filtered
through a 5 Hz, 4th order Butterworth lowpass filter. This filter was
chosen because it approximated the characteristics of the eye to react
E-8
Figure £ ... 2 General View of Test Section
rr1 I
1---' 1-'
t
LASERS LASERS
LT I r I -~ Ia:·· nn i nn I /
WATER PIPE
·~=~·=~=·=!~~;:::::::::.~:~~:·;;;::!:i::::!;:;:J:::l::::;;::::!:;::.:.5:·:*::-:-;::~·~::::~i=~:;:!::.t:::::~!:::::~\::rt~::·:.~·;:=:·!~l~t:::::::::~~\t·(;t:::::~·:=~t:\;tt~i:t~~~-~:;:::;:::::i:;::::::·:::-a;:~:~.t~::.::·:::J::i:;~~;·.:·::::~=::;.:-:~~~:~!
-..-(,1ft CROSS SLOPE)
•• 12ft. •I 12ft. ••
LANE EDGE
Figure E-3 Sketch of Test Setup looking Downrange
to rapidly changing densities. After filtering, the data were recorded
on magnetic tape, strip chart, and digital computer.
Chase Car Instrumentation
As part of the project, two prototypes of mobile transmissometers "" were developed. Such a device would allow the quantitative monitoring of
spray density by a vehicle following or passing the test truck.
The first device was a light beam transmissometer using a white
light source and photodetector over a sensing path of four inches. Upon
preliminary testing of the device it was determined that with the normal
amounts of water from truck spray, the trace would deviate from full
scale by only a few percent. This small amount of deviation was found to
be due to the short measurement path and was determined not to be
sufficient to resolve the small differences in truck treatments.
In the second prototype the measurement path length was increased
and the real world situation of looking through the windshield was
accomplished by mounting a laser inside the vehicle aimed at a sensor on
the front of the hood.
At this stage of development, the mobile transmissometer data is
manually read from strip recorder charts and tabulated. Should the
statistical evaluation determine that this is a viable method, an
automated data collection system could be developed.
Other Test Section Instrumentation
Other test section instrumentation included a calibrated
anemometer which provided remote readout of wind speed (in mph) and wind
direction in degrees, readable to the nearest 10 degrees. A standard
E-12
weather housing contained a thermometer,·hygrometer, and barometer which
were read and recorded each day. Vehicle speeds were measured by a radar
gun mounted in the security car s.ituated about 500 feet beyond the end
of the test section on the north. These sp~eds were reported to the test
conductor after each run. Speeds were maintained, at 55, plus or minus
1 mph for all runs.
E-13
Test Condition~ ...... --As was the case in the preceding study, MVMA prescribed a set of
test matrices; they are summarized in Table E-1. The NHTSA 1-year and
4-year tr~atments as proposed in rulemaking (i.e., 1 year after
adoption, Treatment 3A, and 4 years after adoption, Treatment 2) were
specifically incorporated. Figure E-4 depicts these treatments.
Four different tractors were specified, 6x4* short nose
conventional (S~C), Long Nose Conventional (LNC), Cab-over-Engine (COE),
and a 4x2 COE for a special test of double van trailers. The main study
A involved 16 replications of each combination of treatments and
tractors of the-6x4 type, all to be accomplished with the same van
trailer.
A speci a 1 study B of water depth effects on spray producti o·n was
also set up. In this study, the best performing treatment (anticipated
and found to be 5, all equipment installed} was used on the COE
tractor-van trailer combination.
This study involved 3 water depths: 0.01 to 0.02 inch (shallow),
data from study A with the same vehicle under the same treatments at the
"standard .. water depth of 0.04 to 0.06 inch, and a 11deep 11 water depth of
0.08 to 0.12 inch. Thus any difference in treatment effects with amount
of water available can be studied, at least to the extent of determining
if the relationship is linear or has higher-order components.
*6 wheels, 4 driving
E-14
TABLE E-1 TEST MATRICES.
~ - Main Study
Treatment Phase 1 Aeroaid Steering Case No. Axle
Baseline No
2 6 No Flaps* Skirts**
3 None No Flaps*
3A None No Flaps*
4 9 Yes Flaps*
5 10 Yes Flaps* Skirts-
TRACTOR TYPE
SNC LNC
1 16 runs 16 2 n; 1i; 3 II It;
TREATMENT 3A 16 16 4 16 16 5 16 16
* Monsanto "Spray Guard" Flaps **Schlegel 20/20 "Improved" Skirts
!IYQL! • water Depth
It Treatmen
1
5
Shallow
.01 to .02
16 runs
16
WATER DEPTH
Standard (Stud)' A)
.04 to .06
16
16
STUDY C - Special Vehicle Evaluations SUBSTUDY
Treatment C-1 C2 Tank + LHC Flatbed + SHC
Unloaded Loaded
1 16 16 16
2 or 5 16 16 16
Special Studies
lA: Baseline 1 + Aeroaid SA: Treatment 5 + Side Fairings
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Drive Rear Axle Axle
Plain Rubber Flaps
Flaps* Flaps* Skirts** Skirts-
Flaps* Flaps* Skirts- Skirts-
Flaps* Flaps* Skirts**
Flaps* Flaps* Skirts** Skirts**
Flaps* Flaps* Skirts- Skirts**
CO£
16 All Runs -II II
Van Trailer
16 16 16
VEHICLE: CO£
Deep
.08 to .12
16
16
C3 COE 4x2 + Double Van
16
16
SPLASH AND SPRAY PHASE l[ STAGE A TR·EA TMENTS
1 BASELINE
2 NHTSA (4 yr)
3
3A NHTSA (1 yr)
4
5
I
Figure E-4 Test Vehi.cle Treatments
E-16
~LAIN RUBBER P'LAPS
Study C involves three substudies; C1 is an .-valuation of a tank
trailer hitched to the LNC tractor with a full treatment (NHTSA 4 year)
vs. baseline (no) treatment. C2 is a similar comparison of a flatbed
trailer (loaded and unloaded) with an SNC tractor, and C3 compares a
full (5) treatment with baseline on a 4x2 COE tractor pulling double
vans.
Test Vehicles and Equipment
Splash and Spray Control Equipment
Skirts used throughout this project were supplied by the Schlegel
Corporation. These are flexible filament skirts, each fiber 0.05 inch in
diameter, and designated as Schlegel 11 20/20" spray suppressant skirting.
They are essentially the same as those used in the Phase 1 project
with the exception that the fibers are twice the diameter of those used
in the skirts supplied in Phase 1.
Flaps used in this project were manufactured by the Monsanto
Corporation, under the trade name •• Sprayguard." They consist of stiff
plastic backing on a surface of 11Astroturf" fiber matting which receives
water kicked up by the tires of the vehicle.
Conventional flaps used for the Baseline condition were those
smooth plastic flaps supplied with the trailer when it was delivered to
TTI.
Installation of the spray suppressant materials was carried out in
exact accordance with the NHTSA instructions contained in the proposed
rulemaking. The skirt installation was somewhat modified by following
E-17
the Schlegel recommendations to have the edge of the skirting overhang
the tire tread surface by at least 1 inch.
Figure E-5 gives a composite of installations of the spray control
eq~ipment on a variety of axles of test vehicles.
Stu1y A Vehicles
The-,tractors were all Internati anal. The Cab-over-engine ( COE)
tractor was supplied by Leaseway Transportation. It was a Model 6x4
unit. The Short Nose Conventional (SNC) tractor was a Model F2375 Unit
supplied by Gelco Truck Leasing Co. The Long Nose Conventional tractor
(LNC) was arranged for by International Harvester, through Southwest
International in Dallas, Texas. Both of these latter two units were also
6x4 tractors. The van trailer used throughout all the Study A and Study
B tests was a Hobbs 96 inch by 45 ft standard closed van.
Study B Vehicles
Study 8 used the COE Tractor and Hobbs Van Trailer described above
in this investigation of the effects of water depth on performance of
spray suppressant devices.
Study C Vehicles
In Study C1, the LNC tractor was hitched to a tanker trailer
supplied by the Heil Corporation. In Study C-2, the SNC tractor pulled a
flatbed trailer provided by Hobbs Co. The loaded condition consisted of
chaining two vehicles on the flatbed in such a way as to maximize
turbulence of the airflow around this load at speed.
E-18
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... . .· .. ~- ;_
.. ~ .·--·-·· ~-... ··~ .~:: . . :· ·- . ~ ~ ........ ~ a ,
,~~ ~... .. -'II.·.
-~ -"6 \: ·: 0 ..... •.
c ' e
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-_;;.;.:·7·-·-
E-19
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4-0
,.... 1"0 u Q..
~
E-21
RESULTS
Statistical Methods
A number of questions had to be addressed before the analysis of
the data could be performed. Two of the major concerns are how to
account (adjust) for the effect of wind and what to use as the best
measurement of spray (dependent variable). These considerations are not
independent of one another and applied to all three phases of the study.
Study A
The primary objective of Study A was to evaluate the six
configurations described. Before such an evaluation could take place,
the two primary questions concerning how to account for wind effects and
what was the best measure of spray combining information from all
possible sensors had to be addressed.
Several statistical methods in the form of models were applicable
in assessing treatment effectiveness. Hence, another consideration in
this analysis was the selection of the best or most ·informative
statistical methods to be used. Many models were analyzed.
In the process of analysis, a procedure. or rule was developed
which yielded consistent and logical results for all types of models
considered. This rule involved a definition of the dependent variable
(amount of spray) using linear combinations of only those sensors which
were unaffected by the prevailing winds at the time of the run. This is
called "Rule 4."
E-22
This rule is as follows: select as the dependent variable only
measurements from those sensors providing the best information on amount
of spray produced by the treatment and not affected by the wind
condition at the time of the run. The following choices were used:
1. If the wind condition is in areas 1, 2, or 6, use the geometric means
of sensors s. and 6.
2. If the wind condition is in areas 4, 5, c..r 8, use the geometric means
of sensors 7 and 8.
3. If the wind is a tailwind (areas 3 or 7), use the geometric means of
all four sensors.
4. Figure E-6 depicts this selection rule.
As a further refinement, the natural log of the geometric mean of
the sensors in Rule 4 was actually used in the statistical analysis.
Study B
The primary objective of Study B was to evaluate the effect of
water depth using the baseline and full-treatment configurations only.
Study 8 data was analyied using the partitioned -wind approach and
several dependent variables were attempted, but . this report wi 11 focus
on analyses based on the reconmended procedure for dependent variable
selection as a function of prevailing wind conditions as discussed
above.
Study C
The primary objective of Study C was to compare the amount of
spray produced under loaded and unloaded ccndithms for the baseline and
NHTSA(4YR) configurations on a given truck type - the IH SNC. Since only
E-23
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two configurations were compared as opp.osed to five configurations in
Study- A, the analysis of Study C was similar to that of Study A but on a
reduced scale.
Analysis and Findings
Study A
The results will be reported separately for each of the three
truck types. The statistical method used in -each case varied depending
on the amount of information available for various wind conditions.
Table E-2 summarizes the results for Study A.
Basically, no one treatment was always best. The difference
between full treatment and baseline ranged from 40.6 for the LNC truck
type to 19.4 for the SNC truck typ.e. Full treatment was significantly
better than no treatment and NHTSA(lYR) for COE and LNC. A more detailed
summary of results on each truck type follows.
COE: -Four treatments appear to be about the same. These are full
treatments(S), no steering axle skirts(4), NHTSA(4YR) (2) and no aero or
steering axle skirts(3). NHTSA(lYR) (3A) and baseline(!) form a second
group. The first group is significantly different from the second group
except that NHTSA(4Yr) and no aero and no steering axle skirts are not
significantly different from NHTSA(lYR). All in a particular group are
not significantly different from each other.
E-25-
TABLE E-2 SUMMARY FOR STUOY'A
TRUCK TREATMENT MEAN TRANSMISSION SIGNIFICANT DIFFERENCES (RULE 4)
COE 5 42.9% 4 38.0 Not Significantly Different 2(NHTSA-4yr) 31.9 3 28.1 Not Sig. Diff. 3A(NHTSA-1yr) 23.8 1(Base) 19.1 Not S i g. Oi ff.
SNC 2(NHTSA-4yr} 29.4%
I I 3 28~1 Not Significantly Different
3A(N,HTSA-lyr) 22.7 Not S i g • D i ff.
4 21.3
I Not Sig. Diff.
5 19.4 Not Sig. Diff. 1(Base) 10.0
LNC 4 59.0% I 5 47.5 Not Significantly Different
2(NHTSA-4yr) 26.9 3 24.6
I Not Si g. Di f.
3A(NHTSA-1yr} 23.8 Not Sig. Oiff.
l{Base) 18.4
E-26
~:
For this tractor type NHTSA{4YR) (2) and no aero or steering axle
skirts(3f are not significantly different. NHTSA(lYR) (3A), no steering
axle (4) and full treatment(S) forms a second group. Baseline(!) forms a
third group. Within each group none are significantly different from
each other; between groups all are significantly different from each
other.
~:
The treatment of no steering axl.e skirts(4) and the full
treatment{S) are equally good for this tractor type. A second group
which contains treatments which are all significantly worse than the
above two, but not significantly different from each other, is
NHTSA( 4YR) ( 2) , no aero and no steering axle skirts ( 3), and
NHTSA(lYR)(3A). The baseline treatment is significantly wclrse than all
other treatments.
Study B
The results of this study were that For all dependent variables
the means behave quite similarly over water depths and truck treatments.
One observation that can be made is that the improvement decreases as
the water depth increases. There is a leveling off after the visibility
decreases to a certain level, and as the water depth increases.
Since the baseline responses are initially lower at the low water
depth, the amount of spray tegins to level off faster as water depth:
increases. This would then result in the decreased improvement.
E-27
Study C
LNC TANKER:
Several statistical models were considered for this truck type.
All gave consistent results. They indicate no significant difference
between baseline and NHTSA(4VR} treatments. In all models, baseline had
the larger mean, but was not significantly better.
SNC UNLOADED:
No significant difference was found between the treatments. In
fact, the means were nearly equal.
SNC LOADED:
NHTSA(4YR) treatment is indicated to be significantly better than
the baseline treatment. This held true for all models considered. This
finding must be considered tentative since the data was very different
in amount of variation between conditions •
...&Qf:
All data was used in this comparison. The results indicate no
significant differences between the full and baseline treatments.
Chase Car Results
Modest to low correlations were found among laser readings and
visibility of a target vehicle as observed by occupants of the chase
car, as compared to measurements made with the stationary lasers on the
test section. Sufficiently positive results were obtained to give some
hope that a chase car "real world" measurement system can be developed.
E-28
SUMMARY OF FINDINGS AND RECOMMENDATIONS
Summary of Findings
Answers to Fundamental Questions
Fundamental questions identified by MVMA in their Statement of
Work, will be repeated in different order in this section and answered
on the basis of the results of this project.
GENERAL STATISTICAL QUESTIONS
Is it appropriate to •average• over wind conditions, as reconnended in
the technical report (Phase 1), or does this "averaging" tend to dilute
treatment effects?
Using the mean (either geometric or arithmetic) of all sensor
readings on a run, with no reference to where the wind is blowing the
spray does tend to produce an overly conservative or "diluted ..
comparison of different treatments, which may be misleading. There are
simple methods for _improving and removing bias from the data for the
purpose of comparing treatments. These methods are referred to in this
report as ••Rule 411 which will be sunmarized below.
If •averaging• of sensors is appropriate, is the arithmetic mean the
best measure of this •average .. or is the 11 geometric" mean more
appropriate?
Unless single sensor data is used (a simplification of Rule 4)
some kind of summary statistic is necessary in order to make comparisons
among treatments. 11 Averaging .. or the arithmetic mean is the most
E-29
commonly accepted way of accomplishing a summary number. The geometric
mean, a lesser known summary statistic, fs useful when the distribution
of the data points is known to be other than normally (bell-shaped
curve) distributed. Spray density diminishes as a complex function of
the distance of the sensor from the source of spray; it is not normally
distributed. The geometric mean tends to produce an artificial
"normalization•• of the data, which, as long as it is consistently
applied, should have no biasing effect on the data which are used for
analysis, but rather render that data more suitable for the kinds of
statistical tests (parametric ones) used. Analysis of the data using
both arithmetic and geometric me.ans, in any case, has had no appreciable
effect on the conclusions reached.
How are the conclusions on the effectiveness of splash and spray
suppression devices affected by wind?
By using the double strategy of selection of runs from the ample \
(16) runs made for any given treatment for similar wind conditions, and
by using wind area as a co-variate where selection resulted in too few
runs for valid statistical comparisons to be made, plus the use of Rule
4, comparisons of treatments for spray suppression are not affected by
wind conditions. Wind conditions did not vary systematically enough for
sound comparisons of the same treatment under different wind conditions
to be made. The rule adopted for treatment of the dependent variable
thus rendered the dependent variable invariant with respect to wind.
What is the best statistical method for incorporating the effects of
wind into the treatment evaluation process?
The best method that we have found is the method identified as
"Rule 4", which consists of mapping wind direction and velocity onto a
E-30
polar plot, and then using only those •. >.:msors which are affected most by
the cloud of spray as it is blown to the quarter which the polar plot
identifies. This method of handling wind assumes that the quantity of
water thrown into the air by the tire-pavement interaction is a
constant, and that wind conditions affect where that water thrown into
the air can be found, but not how much. As a further refinement to
correct for different variances; the natural logarithm of the geometric.
mean of the sensors selected by Rule 4 is actually used in the analyses.
It is noteworthy that a much more elementary treatment of data for
windage, that of merely taking the lowest percent transmittance of the
four sensors on any given run, gives very similar results and leads to
similar conclusions. The method of handling the data for wind also calls
for using data with similar wind conditions as much as possible, and
co-varying wind with treatments otherwise. This treatment of the data
app~ars to be very straightforward, takes wind into account in two ways·,
and provides consistent results. The Rule 4 method results in a measure
of spray reduction which is independent of the wind effects at the time
of the run.
STUDY A QUESTIONS
Is visibility significantly improved by adding aeroaids and spray
suppression devices in varying configurations?
In general, yes, but with very important qualifications. Treated
vehicles always produced less spray than untreated (baseline) vehicles,
but these differences were sometimes tr\vial and not statistically
significant. This is a finding consistent with Phase 1 results. How much
improvement was obtained for a given treatment was vehicle-dependent.
All treatmen~s for all vehicles involved flaps on all wheels, except
baseline which had plain flaps on the rear axle only. On COE tractor-van
trai·ler combinations, treatments with aeroaids performed somewhat better
than treatments without aeroaids, but all treatments that involved
skirts on at least the drive and rear axles performed significantly
better than the minimal treatment of installing skirts on the rear axles
only. This treatment. the NHTSA 1-year Rule proposal, was no better than
baseline.
On the SNC tractor-van trailer combination, the aeroaid appeared
to degrade ~pray suppression compared to the best treatment, which was
the NHTSA 4-year proposed treatment, skirts on all axles, no aeroaid.
Deleting the steering axle skirts on this vehicle (as on the COE) did
not make a statistically significant difference, but any other treatment
was significantly less effective in controlling spray. Baseline was
least effective, significantly less so than the NHTSA 1-year treatment.
The LNC tractor-van trailer combinations behaved similarly to the
COE, but with less clear-cut results. The two treatments with aeroaid,
which differed only in whether or not steering axle skirts were present,
performed equally well, and better than anything else. Other treatments
perform about the same among themselves. All treatments were
significantly better than baseline.
Thus in Study A it appears that the NHTSA 4-year treatment
provides reliably better spray control than the 1-year, which tends to
be little better than basel ina. An aeroaid can further help spray
suppression on certain vehicles, but can actually hurt on others, and
thus cannot be considered to be a universal panacea for spray control.
E-32
In the course of running this-study. a source of spray production
was noted that is not affected by any of the treatments so far evaluated
in any of these series of tests. This phenomenon will be described below
under "Other Findings."
Study B Findings
Water depth on the pave!"ent appears to have a reasonably linear
relationship to spray production and its control, such that a given
treatment will provide the same amount of reduction over what would be
produced if no treatment were applied. There may be a point of
diminishing returns as water depth increases, however. At depths where
this might occur, the vehicle is near hydroplane depth (0.25 inch of
water or deeper).
Study C Findings
The final fundamental question asked by MVMA was,
Are splash a.nd spray s,uppression devices statistically more effective
for van semi-trailers than for tankers and flatbeds?
Yes. The NHTSA 4-year proposed treatment of skirts and flaps on
all axles produced no improvement over baseline on an LNC tractor-tank
combination. The amount of spray produced by the vehicle in baseline
configuration with a tanker trailer was comparable to that produced by
that tractor with a van trailer with the NHTSA 4-year treatment. An
unl()aded flatbed trailer does not profit from the application of the • NHTSA 4-year treatment as far as spray suppression is concerned. Without
treatment, such a vehicle produced spray at a level comparable to that
produced by the best of the tractor-van trailers with treatment (LNC),
E-33
and far better ( 1 ess spray) than the same tractor ( SNC) wi t:t, a van
trailer with the best treatment. When a turbulence-producing load was
placed on the flatbed, spray production doubled, but improvements in
spray control with the NHTSA 4-year treatment were only marginally
better than baseline. Thus treatments do not produce nearly as much of a
difference in spray production on trailers other than vans, if these two
trailers are at all representative.
Chase Car Findings
A definite though modest relationship exists between stationary
laser readings of a spray cloud and the extent to which human observers
can discern a target through that cloud. Human observers• reports of
visibility can predict (somewhat) laser readings. A stronger
relationship exists between laser instrumentation in a chase car and
those same indicants of visibility through a spray cloud, but a
paradoxical and low to non- existent relationship can be identified
between stationary laser and moving chase car laser readings. Chase car
instrumentation shows some promise, but it cannot be asserted that the
correct methodo 1 ogy or approach to dat.a reduction has yet been
discovered. Thus the hoped-for breakthrough to permit spray attenuation
devices to be evaluated under highway rather than closed-course
simulated conditions of wet weather has not occurred. There ;s, however,
sufficient encouragement in these findings to pursue the chase car
instrumentation and observation approach further.
E-34
Other Study Findings
A very circumspect evaluation of the effects of an aeroaid without
any other treatment for spray control suggests that with at least
one kind of tractor (LNC) the effects can be major. For a vehicle on
which an aeroaid has a rather negative effect on spray attenuation,
installing of additional devices to smooth air flow and lower air
resistance--side fairings--results in no significant difference. The
results of these two mini-studies point out the very complex interaction
effects of aeroaid, flap/skirt treatment, and cab configuration on spray
generation.
Finally, a phenomenon noted on a casual basis during both studies
should be identified as a potential major source of spray which is
evidently not tre,ated by any of the devices so far developed or
evaluated by anyone: the initial splash from the forward edge of the
steering axle tires. The outward-directed jet of water so produced moves
upward into the slip stream and is transformed into spray which may
play a significant part in the cloud produced by heavy vehicles moving.
over wet pavements on the Nation's highways.
Recommendations
1. Further research and development should be undertaken by industry
to gain a better understanding of the initial splash phenomenon and
to develop treatments to deal with it.
E-35
2. All future evaluations of any splash and spray control treatments
using the stationary laser measurement approach should use the
.. Rule 411 reduction and selection of data to assure comparability
of findings.
3. The instrumented chase car approach to measuring spray from heavy
vehicles should be further explored to find a way to move spray
control device evaluation off the test track and into the real
world.
4. Industry and regulatory agencies at both the state and nation a 1
level should be cautioned not to expect too much from the
installation of skirts and flaps on all wheels. Partial treat
ments may be very disappointing indeed in not producing
perceptible changes so far as the motoring public can see in the
amount of spray generated as compared to no treatment. It may be
necessary to devise a performance rather than a process or
prescriptive standard for spray suppression, since these treatments
are so vehicle-specific and may not work at all on trailers other
than vans. What kind of testing or certification might be suitable
can on 1 y be conjectured , and wou 1 d requ i re much add 1 t 1 ana 1 work •
5. Manufacturers of truck tractors consider aerodynamic gains as a
_major design goal. Trailer manufacturers may well feel likewise.
These designs should include consideration of spray control, and
should be tested for their spray control capability. In the future,
add-on devices for spray attenuation should yield to integration of
E-36
this important function into the overall design of the commercial
vehicles that will be on the Nation•s highways in the 199o•s and
beyond.
E-37
1.0 INTRODUCTION AND BACKGROUND
1.1 Introduction
This report documents a six-month intensive test program in which
a number of different tractor-trailer combinations were equipped with
state-of-the~art sp 1 ash and spray reduction devices and those treatments
eval uate.d. This program was sponsored by the Motor Vehicle Manufacturers
Association (MVMA) of the United States, Inc. In a test program ( 1) that
was a predecessor to that reported here, approaches which had been
developed over the past 10 to 15 years for measuring spray clouds from
heavy vehicles under simulated field conditions were refined. For both
these simulations, test vehicles crossed a water-flooded test pad to
produce a cloud of 'spray which was both photographed, and measured by
means of 1 aser transmi ssometers. This report do·cuments the results of a
second test program.
In both of these test effo.rts, spray reduction devices consisted
of treated back flaps and side mounted valances. The side mounted
valances were flexible fiber .. cat whiskers" skirting over tires. These
devices were provided by Schlegel Corporation as representative of
state-of-the-art for such skirting. "Astroturf" backed flaps,
manufactured by Monsanto Corporation, were used as representative of
state-of-the-art as were aerodynamic fairing devices C'Aeroaids .. )
mounted on the cab roofs of the tractors.
1-1
1.2 Background
Splash and spray clouds raised by heavy trucks have long been a
source of irritation to motorists. Although there is little or no
documented proof that this source of irritation has led to accidents or
fatalities, such circumstances are easily conceivable.
Since the late 1960's, groups such as the Western Highway
Institute, MVMA, and others have tested proprietary designs and generic
ideas to reduce splash and spray. The National Highway Traffic Safety
Administration (NHTSA), early on, proposed rulemaking to reduce the
annoyance and,,;:poss i b 1 e dangers of sp 1 ash a-nd spray produced by heavy
commercial vehicles. However, until the relatively recent introduction
of textured spray suppressing material for flaps and skirting, there
seemed to be no practicable yet effective solution to the problem.
Congress, in the Surface Transportation Assistance Act of 1982,
dec 1 a red •• ••• that vi si bi 1 i ty on wet roadways on the Interstate System
should be improved by reducing, by a practicable and reliable means,
splash and spray from truck tractors, semitrailers, and trailers,"
requiring the Secretary of Transportation to "establish minimum
standards with respect to the performance and installation of splash and
spray suppression devices for use on truck tractors, semitrailers, or
trailers" within one year, and the use of the devices on new vehicles
within two years of the enactment of the law. Devices would also have to
be retrofitted on vehicles in use within five years.
Prior to rulemaking, NHTSA ran a limited number of full-scale
spray-reduction tests at the Transportation Research Center of Ohio. In
these tests, subjects visually evaluated or rated the effectiveness of
the devices tested, rather than the researchers using the objective
1-2
1 aser measuremen~ scheme developed earlier by the Western; Highway
Institute and used by David Weir, then with System Technology, Inc.(2)
The preliminary rating results indicated that device combinations
heretofore believed to be effective did not consistently make a
substantial difference to the naked eye, using subjective ratings as an
indicant. Subsequent MVMA tests at the same site also failed to find
consistent improvements.
In_January of 1984 NHTSA began a new series of tests with Systems
Technology Inc. as contractor at the Firestone test site at Ft.
Stockton, Texas. The methodology used was substantially that of Weir and
his associates. These full-scale tests were designed to achieve
objective measurements and to correlate ·lab test ranking of various
types of spray-suppression devices on various vehicles with these full
scale test results.(3)
MVMA in the interim decided that supplementary tests at a test
site which duplicated the Ft. Stockton approach as closely as possible
would be useful in filling gaps in the NHTSA data. These tests would
ensure that the devices likely to be required by rulemaking would be
practicable, reliable, and effective.
In the period following the conclusion of the MVMA splash and
spray tests, the NHTSA did propose rulemaking.(4) These rules, among
other things, would mandate retrofit and equipping of new vehicles with
skirts and flaps with rated performance characteristics as measured by a
pres_cribed "tunnel" test setup. One year after adoption of the
regulations, heavy commercial vehicles would have to be equipped with
spray suppressant flaps on all axles, and skirts on the rear axle. Four
1-3
years after the regulations took effect, skirts would be required on ill
axles. Aeroaids or other aerodynamic treatments were not mentioned.
Meanwhile, completion of the first MVMA sponsored project, 11 Heavy
Truck Splash and Spray Testing11 ( 1) 1 eft certain questions unanswered.
Among these questions were:
1. Do splash and spray treatmPnts react differently with respect
to depth of water on pavements?
2. Do the best configurations tested on different vehicles in the
original study retain their relative merits in replication; that is, how
reliable are··these relative levels of performance?
3. What relationship does the volume of spray as measured by laser
transmissometer have with how well the driver of a vehicle can see when
trying to pass a spray-generating heavy vehicle?
4. How can splash and spray treatments be tested in the field
under real-world operating conditir~s?
With these considerations (and the proposed regulations by NHTSA),
in mind, MVMA's Splash and Spray Task Force decided to fund further
studies. In these studies the top vehicle treatment configurations, plus
NHTSA proposed treatments (where different), would be subjected to
rigorous testing, with sufficient trials of each configuration to assure
that adequate statistical analysis of the data could be done.
1.3 Objectives
The 1985 test project had the following specific objectives:
1. To supplement data already available and to analyze the
aggregate data set to provide a basis for reasonable and effective
1-4
actions for addressing the problem of splash/spray reduction from
tractor-trailer combination vehicles;
2. To obtain sufficient test runs on each vehicle treatment
configuration to assure adequate statistical analysis of the data, and
both valid and reliable conclusions;
3. To obtain test data on the effects of treatments on trailers
other than van-trailers, but proposed for treatment by NHTSA;
4. To investigate methods by which reliable spray, measurement data
could be obtained under highway conditions; and
5. To analyze the test data in the 1984 Ft. Stockton test
sponso~ed by NHTSA and re-analyze the Phase I MVMA study using analytic
methods developed on this project to permit comparisons to be made among
all three studies.
These objectives realized will permit answers to the following
questions posed by MVMA:
a. Is visibility significantly improved by adding aeroaids
and spray suppression devices in varying configurations?
b. Are splash and spray suppression devices statistically
more effective for van semi-trailers than far tankers or
flatbeds?
c. How are conclusions on the effectiveness of splash and
spray suppression devices affected by wind?
d. Is it appropriate to "average" over wind conditions, as
recommended in the Phase I Report, or does this .. averaging"
tend to dilute treatment effects?
e. What is the best statistical method for incorporating the
effects of wind into the treatment evaluation process?
1-5
f. If "averaging" of sensors is appropriate. is the arithmetic
mean the best measure of this "average" or is t.,e "geometric"
mean more appropriate?
1-6
2.0 t'EST PREPARATION
2.1 Layout and Test Surfaces
Figure 2.1-1 provides a general plan of the test section through
which the splash and spray control equipped vehicles passed on every
run. The asphaltic concrete test pad surface which was installed in the
Phase 1 tests reported last year (1) was once again used, but was
supplemented by a strip of Jennite (coal tar) coating which was laid
down on top of the original portland cement aggregate surface of the
airbase apron. This supplementary surface had similar texture
characteristics, but considerably different skid number and hence
microstructure characteristics, a.s can be seen in Table 2.1-1 .• The
supplementary surface measured 12 x 660 ft, and was located south of the
original (and primary) test surface. The water distribution system, laid
down on the east (upslope) side of the test section, consisted of 4-inch
pipe supp 1 i ed by a T Junction through a va 1 ve in each branch of the T.
The PVC pipe was drilled with an 1/8-inch hole every two feet to deliver
the hydrant-supplied water to the surface of the test section. The water
supply was adjusted to provide the proper surface water depth on each
pad throughout testing. Water depth measurements were taken at six
locations by the use of NASA tye..e water depth gauges. The nominal water
depth maintained during all testing was 0.04 to 0.06 inch on the north
(original) pad, except during Study B, which studied water depth
differences (see section 3.1). Local irregularities and the
south-inclining surface of the air base apron precluded uniform water
depth maintenance on the south test surface. TTI and the Splash and
2-1
N I
N
Target V•hlcle
T 72'
"'Paaalng• ~ Cone • .. . . . o''!!:!:" , .. • . .. • ··. . -.-ot TRAVIL • • ·
~ !- "!' •
La a era ~ L Detector• ffiVIdeo Houae La a era~ L Detector•
JENNITE SURFACE ASPHALT SURFACE
1-4 1-4 &-a s-a
Water Line
Teat Trailer I I
,___J ~ ·I ·I ·I •I ·I •I ·I H •I ~ 1 450' 500' 660' 88&' 800' 840' 880' 1875'
NORTH
Figure 2.1-1 Ge·neral Layout of the Test Section
TABLE 2.1-1 TEST SECTION SURFACE CHARACTERISTICS
SURFACE SKI 0 NUMBERS * TEXTURE_
Rib Tire{ESOl) Smooth Tire(E524) Mean so Mean so
.., .. ~
North Pad: Asphaltic Concrete 62.5% 2.1% 19.8 1.1 0.029"
South Pad: Jennite over Cement 36.9 3.0 12.8 1.0 0.028"
*Measured by standard locked wheel skid trailer-ASTM Procedure E174
2-3
Spray Task Force of MVMA, agreed to let this surface "float" at a depth
not greater than 0.20 inch to represent a somewhat road polished highway
surface with puddles. Thus water depths varied over this surface from
near-hydroplane depth (0.20 inch) to nearly dry. This may be somewhat
repr~esentative of a "real world" uncontrolled condition.
Four laser transmissome.ters were located inthe south section and
four more lasers were located at the exact locations used in the 1984
tests on the north section. In all the data to be reported here, Lasers
1 and 2 were on the west side of the south section, Lasers 3 and 4 were
on the east side of the south section, Lasers· 5 and 6 were on the west
side of the north section, ·and Lasers 7 and 8 were on the east side of
the north section. In the 1984 Phase I tests, laser positions 5 and 6
were designated 3 and 4, and 7 and 8 were 7 and 8. The two laser
locations were situated 490 feet apart.
The test trailer from which all runs were controlled was located
in approximately the same spot as in 1984, about 100 feet from the test
section on the east side. A~small metal building was situated midway
along the test section, and just off the vehicle path. This building,
called the Video House, contained the remote video camera and equipment
for making vehicle configuration changes.
No reference checkerboards were used in these tests; since
photography was not considered to be the major method of documentation
that it was in 1984.
A reference mark for the chase-car occupants to begin their
procedures was located just south of the jennite-coated surface, at the
spot designated "Passing Cone" in Figure 2.1-1. A 1975 Buick, the target
vehicle used for chase car observers to judge visibility, was located 72
2-4
feet from the vehicle path to the west, and .L975 feet from the Passing
Cone. This car is pictured in Figure 2.1-2. A general view of the test
section, taken from an elevated position to the northeast, is provided
in Figure 2.1-3.
2.2 Instrumentation
2.2.1 Video Coverage
The primary pictorial coverage on this project was videotape (with
audio). This coverage was in color. Two camera and recorder setups were
used. One camera was situated uprange from the north laser set, 265 feet
distant and on the east side of the vehicle path. This location
approximated that used for downrange still photography on the right side
of the vehicle in the 1984 tests. The passage of the vehicle was
recorded by the test conductor on each r:-un.
The other camera was located in the chase car, situated such that
it could record the view out the windshield of this vehicle as it
tracked the test vehicle at a distance of 100 feet. See Figure 2.2-1.
Slate numbers were affixed to the back of the test vehicle (Figure
2.2-2) to annotate this coverage, which is in monochrome and silent.
Chase car occupants operated the recorder for this coverage.
2.2.2 Laser Transmissometers
Quantitative spray density data were measured by means of eight
low power lasers (5 mw) aimed, parallel to tte vehicle path, at photo
detectors or light meters. To account for crosswind, t~o lasers were
located symmetrically on each side of each test track at two locations
2 ... 5
Figure 2.1-2 Target Vehicle
~~~::~. :"~: " .... . --~~:· .. -'"''.":"~ . ··~:·~-:-:-..;:=' .. . . ....
"' ..... J~ ..... ~
> - __ .... -- .....___t ..... -~ :
Figure 2.1-3 General View of Test Section
2-7
Figure 2.2-1 Chase Car Interior
Figure 2.2-2 Rear End of Tank Trailer Showing Slate Number Board
2-9
as described above. The 1 asers were 1 ocated 50 ft from the detectors as
shown in Figure 2.2-1. The lateral and vertical plac~ment is shown in
Figure 2.2-3 with the lower inside location duplicating the position in
previous work. The positions represent a passenger car eye height {3.75
ft) and the height used by the NHTSA {3 ft) in previous tests.
Tr~ lasers and detectors were mounted in custom made enclosures to
provide water proofing and ruggedness {Figure 2.2-4 and 2.2-5). The very
rugged mounts did not permit any motion of the laser beam due to air
blast or pavement vibration which could produce ambiguous data. Tests
were run to determine this effect by passing trucks by without water; no
adverse effects were noted. An innovative lens system was developed at
the detector end to focus the 0.75-inch spot back to a pinpoint on the
10 111t1 photocell. This technique eliminated the signal noise of some
previous tests due to nonuni fo.rmi ty across the beam and beam motion due
to air density changes.
2.2.3 Sase Station Data Processing and Reduction
The signals from the detector were displayed on meters at the
detectors for alignment and then sent to the telemetry system in the
control trailer. The eight signals were transmitted via radio to a
permanent base station as shown in Figure 2.2-6. At the base station
(Figure 2.2-7) the data were first filtered through a 5 Hz, 4th order
Butterworth lowpass filter. This filter was chosen because it
approximates the characteristics of the eye to react to rapidly changing
densities. After filtering, the data were recorded on magnetic tape,
strip chart, and digital computer. The strip chart provided
instantaneous analysis of data quality before the next run was made. A
2-11
N I t-' N
t
LASERS LASERS
~( 1 ~ CROSS SLOPE)
I -t 1 2 ft. •I c 12 ft. ...
LANE EDGE
Figure 2.2-3 Sketch of Test Setup looking Downrange
-y ---
Figure 2.2-4 Lasers and Sensors Looking Downrange
Figure 2.2-5 Inside View of Sensor in Cost Effective Enclosure
2-13
N g
t-1 Ul
120 VAC
•. Ill( 50 FT .... I
5MW ••-~-~ LASER
TEST TRACK
I
(ONE OF EIGHT)
I ... PHOTO -
2 -
DETECTOR ~ .
3 -
'[ - 4 -
METER 5 6 . 7 8 --
POWER SUPPLY -
Figure 2. 2-6 Test Secti.on Te 1 emetry Setup
~
TELEM.ETRY TRANSMITTER •·
---_.
-ANTENNA
1/2 MILE YTO BASE STATION
N I ...... m
'I ~ ~-. ~ -~ -~ -· -
I I .. 5 H·z -- FILTER -2 ~
TELEMETRY - SUBCARRI,ER 3 --RECEIVER DISCRIMINATORS 4 '~
5 14 TRACK 6 MAGNETIC 7 TAPE
8 ,
12 CHANN·EL STRIP CHART
BASE STATJ.QN
Figure 2.2-7 Base Station Signal Processing and Recording Setup
,, 8 CHA,NNEL ANALOG TO
' DIG,ITAL
MICRO-COMPUTER I
I
I
PRINTER
typical strip chart trace of one transmi s.someter channf:al is shown in
Figure 2.2-8 with the truck starting to pass at 1 second producing a
minimum value of 7 percent. The digital computer provided a summary
printout of the minimum light transmission from each laser based on zero
and 100 percent calibrations just prior to each run. The computer
printout of percent transmission for-each laser, shown at its relative
location on the test section, was available within seconds after each
test run {Figure 2.2-9).
The laser system received an end-to-end calibration by inserting
precision· neutral density fi 1 ters of 12 percent, 25 percent, and 50
percent in each laser beam and observing the digital output values,
which were nominally within 2 percent of the true filter values.
2.2.4 Chase Car Instrumentation
As part of the project, two prototypes of mobile transmissorneters
were developed. Such a device would allow the quantitative monitoring of
spray density by a vehicle following or passing the test truck.
the first device was a light beam transmissometer using a white
light source and photodetector over a sensing path of four inches. This
device, shown in Figure 2.2-10 was attached to the hood of a standard
size 1979 Pontiac station wagon at the location of the hood
ornament. The photocell output was amplified and displayed on a strip
chart recorder. An unobstructed beam of light produced a full scale
deflection of 50 nm, and fully occluded would produce a zero chart
reading. Upon preliminary testing of the device it was determined that
with the normal amounts of water from truck spray, the trace would
deviate from full scale by only a few percent. This small amount of
2-17
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2-18
N I ..._.
4.0
HUN NUtiBER: 207
WIND SPEED: 13 MPH
(5) 30.2 i.
( 1 ) 1 0. 4 /~
... ~
TEST RESULTS <PHASE II>
[tATE: 6/4/85
DIRECTION: 160 DEG
TRUCI\ • /I\ I I
<o> 12 i~
ASF'HAL T
(2) 3 7.
JENNITE
' ! t I !
' ! ' ' !
<7> 81,4 4
(3) 83.7 i.
<B> 95.1 X
(·\) 98.7 i~
figure 2.2-9 Typical Computer Printout of Run Results
. . · • il -
~..-;,:;.; ··et-iNz."'i'ki'k: .. ~:JI1i' _. I
l: c
Figure 2. 2-1 0 Drop 1 et De teeter Prototype
Figure 2.2-11 Laser Transmissometer Sensor Mounted on Hood
2-21
deviation was found to be due to the short measurement path and was
determined not to be sufficient to resolve the small differences in
truck treatments. In an attempt to improve the resolution of the device,
an electronic track-hold circuit was developed which would track the
full scale reading and on command hold that reading as a datum. The
difference voltage between the datum and spray attenuation was highly
amplified and displayed on the chart. Even though there was about a
tenfold improvement in resolution, it was felt tnat small differences
would still be lost due to the signal to noise ratio.
In the second prototype the measurement path length was increased
and the real world situation of looking through the windshield was
accomplished by mounting a laser inside the vehicle aimed at a sensor on
the front of the hood (Figure 2.2-11). In order for the beam path to be
as close as possible to the driver•s site path, the laser was located on
the •s• pillar near the roof. The beam was aimed through the part of the
windshield covered by the windshield wipers. The laser beam intensity
was measured by a one em silicon photoelectric ce)l located in the end
of a three-inch-long plastic tube, approximately five feet in front on
the windshield. The inside of the tube was pa~nted flat black to reduce
any ambient light effects. As in the first prototype, the cell output
was amplified and displayed on a strip chart recorder. A typical trace
shown in Figure 2.2-12 shows the zero and 100 p:rcent transmission
calibrations along with an actual test run. The effect of the wipers
cutt~ng the beam can be easily seen, as can various levels of
attenuation between wipes due to spray in the beam path and buildup on
the windshield; this is just as the driver sees.
2-23
0
100 per cen
CAliBRATION
N I
N +::-
0 per cen
OBSERVER 2 TRACE
lASER DATA BEGINS PASSING CON£ EVENT MAR/ L
~s (10 Sec.)
Figure 2.2~12 laser and Observer Event Mark Recording (Typicdl)
At this stage of development, the mobile transmissometer data is
manually read from the charts and tabulated. Should the statistical
evaluation determine that this is a viable method, an automated data
collection system could be developed.
2.2.5 Other Test Section Instrumentation
Other test section instrumentation included a calibrated
anemometer which provided remote readout of wind speed (in mph) and wind
direction (in degrees), readable to the nearest 10 degrees. A standard
weather housing contained a thermometer, hygrometer, and barometer which
were read and recorded each day. See Figure 2.2-13 for the location of
this instrumentation. Vehicle speeds were measured by a radar gun
mounted in the security car situated about 500 feet beyond the end of
the test section on the north. These speeds were reported to the test
conductor after each run. Speeds were maintained at 55, plus or minus
1 mph for all runs.
2-25
Figure 2.2-13 Test Section Anemometer and Weather Station
2-27
3.0 TEST PLAN
3.1 Test Conditions Matrix and Rtin Record
As was the case in the preceding study, MVMA prescribed a set of
test matrices; they are sumnarized in Table 3.1-1. These treatments
differ from those originally called for in the MVMA request for
proposal, but reflect the results of several Splash and Spray Task Force
and TTl meetings. The NHTSA 1-year and 4-year treatments as proposed in
rulemaking (i.e., 1 year after adoption, Treatment 3A, and 4 years after
adoption, Treatment 2) were specifically incorporated. Figure 3.1-1
depicts these treatments.
Four different tractors were specified, 6x4* Short Nose
Conventional (SNC), Long Nose Conventional (LNC), Cab-over-Engine (COE),
and a 4x2 COE for a special test of double van trailers. The main study
•• A .. involved 16 replications of each combination of treatments and
tractors of the 6x4 type, all to be accomplished with the same van
trailer.
A SJ,;eCial study usn of water depth effects on spray production was
also set up. In this study, the best performing treatment (anticipated
and found to be 5, all equipment installed) was used on the COE
tractor-va •• trai 1 er combination.
*6 wheels, 4 driving
3-1
TABLE 3.1-1 TEST MATRICES STUDY A - H~in Study
-Treatment Phase 1 Aeroaid Steering Case No. Axle
1 Baseline No
2 6 No Flaps* Skirts**
3 None No Flaps*
3A None No Flaps*
4 9 Yes Flaps~
5 10 Yes Flaps* Skirts**
TRACTOR TYPE
SHC LNC
1 16 runs 16 2 m II 3 II !I
TREATMEHT 3A 16 16 4 16 16 5 16 16
• Monsanto •spray Guard• Flaps {751 Level) **Schlegel 20/20 "tmprovect• Skirts ***OEM Device
SIUDY B - Water De,th
Treatmen
1
5
Shallow
t .01 to .02
16 runs
lD
WATER DEPTH
Standard {Study A)
.04 to .06
16
16
STUDY C - Special Vehicle Evaluations SUBSTUDY
Treatment C-1 C2 Tank + LHC Flatbed + SNC
Unloaded Loaded '
1 16 16 16
2 or 5 16 16 16
Specf a 1 Studies
lA: Baseline 1 + Aeroaid using LNC +Van SA: Treatment 5 + Side Fairings using SNC + VAN
3-2
Drive Rear Axle Axle
Plain Rubber Flaps
Flaps* Flaps* Skirts** Skirts**
Flaps* Flaps* Skirts** Skirts**
Flaps* Flaps* Skirts**
Flaps* Flaps* Skirts** Skirts**
Flaps* Flaps* Skirts** Skirts**
CO£
16 All Runs -Ii
Van Trailer !I 16 16 16.
VEHICLE: COE
Deep
.08 to .12
16
16
C3 COE 4x2 + Double Van
16
16
SPLASH AND SPRAY PHASE :0:
1 BASELINE
2 NHTSA (4 yr)
3
3A NHTSA (1 yr)
4
5
STAGE A TREATMENTS
® <® I PLAIN R~BBER FLAPS
Figure 3.1-1 Test Vehicle Treatments
3-3
This study involved 3 water depths: 0.01 to 0.02 inch (shallow),
data from study A with the same vehicle and the same treatments at the
"standard" water depth of 0.04 to 0.06 inch, and a "deep" water depth of
0.08 to 0.12 inch. Thus any differences in treatment effects with amount
of water available can be studied, at least to the extent of determining
if the relationship is linear or has higher-order components.
Study C involves three substudies; Cl is an evaluation of a tank
trailer hitched to the LNC tractor with a full treatment but no aeroaid
(NHTSA 4 year) vs. baseline (no) treatment. C2 is a similar comparison
of a flatbed trailer (loaded and unloaded), pulled by an SNC tractor,
and C3 compares a full treatment (5) with baseline (1) on a 4x2 COE
tractor pulling double vans.
Two special mini-studies were also done, involving only 5 runs
each; the first used the (lA) baseline treatment but with an aeroaid to
get direct observations of the effects of the aeroaid on the COE
tractor. Since side fairings were also provided as stock equipment on
the SNC, these were added to the full treatment 5 to form SA to assess
if these devices added anything to spray attenuation performance.
Table 3.1-2 provides the run record for all data obtained on the 3
studies. Since treatments, except for baseline, consist of variations in
skirt placement, skirt locations are designated. "Aeroaid" consists of
whatever the. stock unit supplied with the tractor. Any special
conditions are noted, and then dates and run numbers are identified. The
reader can directly cross-reference this run record with the data
collected on each run by run number in the compilation of all runs in
Appendix A.
3-4
ST\DY TMCTDit TRAJL£R ~:·TREATMENT AERO SPECIAl. COHOITIOitS DATES RUN NO's REMRkS
SICIRT Ri. Uiir IJrl·v• ~~ ... ,.
A COl VAl ' 1 No 5·23·85 t-5 BAS£ 5-27 61-66 5-28 97-101
2 X X l No 5-23 6·10 NHTSA-•yr. 5·27 55·60 s-2a 77-81
3 I l ... 5•23 15·20 5-27 37·42 5-28 92·96
3A l ,.. 5-23 5·27
llo15 NHTSA•lyr. 31·36
5-28 87·91
4 X X , .. 5-23 21·25 5-27 43·48 5-28 67·71
5 l l X , .. 5-23 26·30 5·27 49·54 5-21 7%-76
A S1IC VAll 1 ,.. 6·03 176-180 BAS£ 6-04 236·241 6-05 257-261
z l X X ,.. 6·03 181-185 HHTSA-4yr. 6-o.t 230-235 1-05 263-267
1-03 191-195 Q
3 X X Ho ~ 6-cM 212·217 8 6-05 273-2'17
• I ,.. 1-03 181-1,., HHTSA-IJr. """ 1-04 201-211 0:: 1-01 2A-17Z
~ 4 l l , .. I-OJ 191-200 .... 211-223 a:
.... os 242·24& Q
5 X X X , .. 1-03 201·205 ~ &-04 224·221 ~05 ~47·251 ><
SA I l I Yli st• i!•lrl1191 '!;ec~&r• ..... -, "'!2-2!1 cr: A LJC VAl Ho 1-11 311-315 BASE .....
1-14 358-36Z ~ .... 7 JH-.401
2 X I I ... ... 11 311-320 llfJSA-4yr. ..... z
1-14 3&3-367
~ 5-17 402-407
3 I X ... 1-11 327·331 L5· 1-14 368-372 1-17 384-389 a: .....
lA l ... 5-11 321·321 NNfSA-lyP • 1-14 373-377 lol7 371-313 N
I 4 I I , .. 5-11 332-337 .... ..... 343-347 •
5-17 390-395 C"')
5 I I I , .. 1-11 331-ll2 """ ....J 1-14 348-352 CCI t-17 391-401 .:
1A .. 'I'll 1-14 353-357 •s,.ct•J•
• COl VAl 1 .. ....... O.,tla .01-.02 s-a 102-lOt USE S..lO 160-167
....... O.,tlt ..... 12 5-21 131·143 S..lO 152·159
lA . ,. w.w ""*" .ot-.oz 5-21 110.114 •s.-:1a1• -- ,.,... .oe-.12 5-21 131-135
I l l I ,. Water o.,ttt .oa •• oz s-n 115o12Z S..lO 158-175
Water O.,tla oQI.oll 5-21 123·130 SolO 144·151
,c& uc TMI 1 . . . .. 1-10 287·302 lASE 2 l l l ... 1-10 278-286 NHfSA-4yr.
303-310
ez SIC FUr ... lhtloadld S.20 422-429 SASE 438-445
Loaded S.Zl 446-453 470..76
2 X X l ,.. Unloaded 1-20 414-421 HHTSA-•yr. 430-437
Loaded S.Zl 454-461 462-469
COl DOUIU ... 1-24 486-501 BASE YAII.
5 I I l '" Sktru on RHr S.Z4 478-485 Trat ler 1, Dol Jy 502-509 Traf Jer z. Flaps on all Axles
3.2 Test Vehicles and Equipment
3.2.1 Splash and Spray Control Equipment
Skirts used throughout this project were supplied by the Schlegel
Corporation. These are flexible filament skirts, each fiber 0.05 inch in
diameter, and designated as Schlegel "20/20 11 spray suppressant skirting.
They are essentially the same as those used in the Phase 1 project (1)
with the exception that the fibers are twice the diameter of those used
in the skints supplied in Phase 1. Lengths (top to bottom) were all
· 11-1 nch.
Flaps used in this project are identical to those used in Phase 1,
in fact in some cases the same flaps we.re used again. These devices are
manufactured by the Monsanto Corporation, under the trade name
"Sprayguard." They consist of stiff plastic backing on a surface of
"Astroturf .. fiber matting which receives water kicked up by the tires of
the vehicle.
Conventional flaps used for the Baseline condition were those
smooth plastic flaps supplied with the trailer when it was delivered to
the Bryan Research and Extension Center.
Installation of the spray suppressant materials was carried out in
accordance with the NHTSA instructions contained in the proposed
rulemaking (4); these instructions and pertinent installed dimensions
can be found in Appendix C. The skirt installation was somewhat modified
by following the Schlegel recommendations to have the edge of the
skirting overhang the tire tread surface by at least 1 inch.
3-6
Figure 3.2-1 gives a composite of ins;tallations of the spray
control equipment on a variety of axles of test vehicl~s.
In order to install this equipment without damage to the vehicles,
small C-clamps which can be discerned in these figures, were used
extensively.
3.2.2 Study A Vehicles
·study A vehicles are pictured in Figures 3.2-2, 3.2-3, and 3.2-4.
The tractors were all manufactured by International Harvester Company.
The Cab-over-engine (COE) tractor was supplied by Leaseway
Transportation. It was a Model C09670, 6x4 unit. The Short Nose
Conventional (SNC) tractor was a Model F2375 Unit supplied by Gelco
Truck Leasing Co. The Long Nose Conventional tractor (LNC) was a model
F9370 arranged for by International Harvester, through Southwest
Internati o·na 1 in Da 11 as, Texas. Both of these 1 atter two units were a 1 so
6x4 tractors. The van trailer used throughout all the Study A and Study
B tests was a Hobbs 96 inch by 45 feet standard closed van. Additional
information on these vehicles can be found in Appendix B.
3.2.3 Study B Vehicles
Study B used the COE Tractor and Hobbs Van Trailer described above
in this investigation of the effects of water depth on performance of
spray suppressant devices.
3.2.4 Study C Vehicles
In Study Cl, the LNC tractor described above was hitched to a
tanker trailer supplied by the Heil Corporation. This vehicle is
3-7
_,.; I ..0
1\ !' -·\_-D . "" {
~ '
' -
\ · ..
i .. ____ J -~~ \ '~"lb ..... I
0
1~\ \\U\~ Houston, u
:G' "'..-'
I
. lUI_:
~ a~:'
"''- C./ . . -
I ! ~ " • •
~
..... t;. -~? :~":j::;:_:_ ~ .. ,:~ ...
_, ..... ~~~-.... ....J
Figure 3.2-1 Typical Installations of Spray Control Equipment
Figure 3.2-2 Cab-over-engine (COE) Tractor
Figure 3.2-3 Short Nose Conventional (SNC) Tractor with Van Trailer
1-11
Figure 3.2-4 Long Nose Conventional (LNC) Tractor with Van Trailer
'I
Fi·gure 3.2-5 LNC Tractor and Tank· Trai·ler
-pictured in Figure 3.2-5. In Study c~2, the SNC tractor p~lled a flatbed
trailer provided by Hobbs Co. Figure 3.2-6 shows this trailer in an
unloaded condition. The loaded condition (Figure 3.2-7) consisted of
chaining two vehicles on the flatbed in such a way as to maximize
turbulence of the airflow around this load at speed. A Chevrolet 3/4 ton
pickup was installed rear end foremost, with the tailgate down, at the
forward end of the trailer. A crash test Honda sedan was loaded on the
.·ear of the trailer, and turned 90 degrees to the direction of vehicle
travel.
Study C-3 used a vehicle combination very similar to that used in
Phase 1 testing, a Ford COE 4x2 tractor hitched to two "double pup"
short van trailers connected with a dolly. This vehicle was provided by
Central Freight Lines of Waco, Texas. It is pictured in Figure 3.2-8.
Note that both this tractor and the SNC were supplied with short front
bumpers. ln order to make their aerodynamic configuration comparable to
the other tractor which had full front bumpers, the SNC and the Ford
were equipped with a custom-made wooden plank that was full-width.
Details on these test vehicles in Study C may be found in
Appendix B.
3.2.5 Special Studies
A minimum 5 runs with the Study A LNC tractor and van trailer were
made with the vehicle equipped with its aeroaid, but otherwise in
Baseline {Treatment 1) condition. Five more runs were made with the
Study A SNC in full Treatment 5 configurat~on, but with side fairings
a 1 so in p 1 ace •
3-15
Figure 3.2-6 SNC Tractor with Unloaded Flatbed Trailer
Fi'gure 3.2-7 Loaded Flatbed
3-17
Figure 3.2-8 COE Tractor with Double Van Trailers
3-19
3.3 Test Run Procedures
3.3.1 Grbund Rules
The ground rules governing Phase II testing were substantially the
same as those in effect during the initial splash and spray testing
project. Some modifications were made based on the experience gained
during previous tests and to accommodate differences in test conditions.
1. Wind velocity did not exceed 20 mph (avg. velocity). Gusts up to
22 mph were acceptable if occurrence was less than 50 percent of
the time. Wind direction was constrained to that southern half of
the compass between 90 and 270 degrees. Winds consistently into
the north half were grounds for a hold or scrub.
2. Precipitation during testing sufficient to be detected by laser
instrumentation was an automatic hold. Testing conmenced at any
time that precipitation stopped, if water depth criteria could be
attained.
3. For Studies A and C, water depth as measured by a NASA water
depth gauge did not average less than 0.04 inches nor more than
0.06 inches. The nominal deep and shallow water depths for
Study B were respectively double and half that of the Study A and C
depths. No attempt was made to control water depth on the South
test surface.
4. The University Weather Service prediction of precipitation and
wind velocity and direction available at or about 4:30 p.m. on
the day preceding a test day governed the Test Condutor•s
deici~ion whether to run or scrub.
5. Each set of passes by the Test Vehicle and Chase Car constituted
3-21
a run which was assigned a unique TTI run number. A test aborted
or incomplete for any reason still carried that TTI run number.
A corrective or additional test with the same MVMA test
configuration number was assigned a new TTI run number by the
Test Conductor.
6. A mi-nimum of five minutes elapsed between each test run to
permit water depth on the test surface to stabilize.
7. Tests were conducted during the time 30 minutes after sunrise to
30 minutes before sunset to insure that light was adequate for
photography and chase car observers.
a. Safety Rules in effect for all vehicle testing in Bryan
Research and Extension Center (BREC) applied to this test project.
9. The Test Conductor had sole authority for all test runs and for
decisi-ons to abort, hold, or scrub any test run. All Test Team,
Industry, and Government observers were subj(.:t to the Test
Conductor's authority during test preparations and runs. The
Chase Car Driver had authority to abort the chase car pass for
safety reasons.
3.3.2 Test Section Procedures
1. The truck driver positioned himself approximately 1 mile south of the
test section, and waited for a "go" from the test conductor. The test
conductor verified that test section support persennel were ready, and
no intruding traffic was evident. During this waiting period, chase car
personnel changed the slate number board on the back of the test vehicle
trailer and calibrated the chase car laser transmissometer.
3-22
2. Laser transmissometers were calibrated just prior to each run.
Jhrough radio coordination with the base station, the laser beams were
::caused to be occluded by remote control from the test trai 1 er and the
'instrumentation was adjusted for "zero" 1 ight transmission by the base
station technician. Then the laser beams were allowed to strike their
respective photoreceptors while the base station technician adjusted the
instrumentation to reflect a 11100 percent" light transmission condition.
3. The truc.k driver was then instructed to begin the run, which called
for him to quickly accelerate the vehicle to a steady 55 mph velocity,
and pass from south to north through the test section. Reference lines
helped him maintain a position through the test section such that the
middle of vehicle was exactly 8 feet from the nearest laser on each
side. The chase car followed at a distance of 100 feet, directly behind
the test vehicle.
4. As ~he test vehicle neared the test section, the test conductor
called for the master data recorder (an FM data acquisition tape
recorder) to be turned on. Then he annotated the master recorder with an
announcement of the run number and other identification information, and
turned on the video recorder. As the vehicle reached the test section,
the test conductor called for the strip chart recorder at the base
station to be initiated by saying "visi(corder) on."
5. By watching a laser photocell voltage readout in the test trailer,
the test conductor could determine exactly when the vehicle was in the
main test cell. At that moment, he read the anemometer displays in front
of him, and remembered the readings for later recording.
6. As the laser photocell output returned to normal (light no longer
occluded by spray), the test conductor called for the run to be
3-23
complete, which was the signal for the base station tecnnician to begin
the computer routine to output test results. The test conductor then
shut off the video recorder, announced wind data, and wrote the reported
vehicle speed in the test log along with other pertinent data.
7. The test conductor the- noted what the test configuration was to be
for the next run, gave appropriate instructions for the truck ol·i ver to
return to the starting point or to proceed to the configuration change
area (near the video house) for a change in the splash and spray
equipment. Water depth was checked every 5 to 10 runs with a NASA water
depth gauge. Five minutes or more separated each test run to assure that
water depth on the surface returned to normal.
3 .3 .3 Chase Car Procedures.
The chase car crew consisted of the chase driver and two
in-vehicle observers.
Upon receiving the "GO" signal from the test conductor, the chase
driver accelerated directly behind the test vehicle such that the chase
car matched the test vehicle speed (55 mph) and maintained ~ 100 foot
gap. The driver was assisted in maintaining the constant distance
between vehicles by keeping the fiducial mark on the rear of the test
trailer centered between the reference marks on the chase car
windshield. In addition to operating the chase car, the chase driver
provided a verbal "PASSING'' signal to the test observers when the chase
car drew even with the "PASSING CONE, .. located up-range from the first
set of spray sensors.
Throughout the beginning of each test run, the in-vehicle
observers fixated on the fiducial mark on the back of the truck trailer
3-24
until such time as they received the signal that they were "PASSING" the
test vehicle (the chase car did not in fact pass the test vehicle). Upon
hea·ring the passing signal, the observers immediately looked downrange.
As soon as an observer saw the "ON-COMING 11 (target) vehicle positioned
downrange, he or she depressed a hand-held event switch. The observers
kept the event switch depressed as long as the target vehicle was in
sight through the spray cloud. When the target vehicle was not visible
the observer released the switch. He or she remained alert to depress
the switch whenever the target again became visible. These ev~nt marks
were recorded on the on-board recorder and appeared as light onsets on
the video record from the chase car. See Figure 2.2-12 for a typical
record of a chase car test run.
In addition to the duties above, the in-vehicle observers were
responsible for slating the correct test run number on the rear of the
test vehicle prior to each run and operating the on-board
instrumentation and video immediately prior to and after each run •
..... _ .......... ....-.;,.-..-,. ... ··l'l~~;-.·'":'·•·'"'" ... ·.~-
3-25
4.0 STATISTICAL METHODS AND RESULTS
This section will contain a detailed explanation of the statistical
methods used {Section 4.1), the results (Section 4.2), and the summary and
conclusion, Section 4.2.4·fbr each phase of the splash and spray study (Studies
A, B, and C). Saction 4.2.4· will also outline a recorrmended standard procedure
for analyzing splash and spray studies. The reader who is primarily
interested in the results and proposed method of analysis may wish to proceed
directly toSectioni4.2.4"0etailed analysis (e.g. computer runs and plots) are
contained in the Appendix of Volume 2.
4.1 Statistical Methods
This section will contain a summary of the statistical methods for
studies A, B, and C. A number of questions had to be addressed before the
analysis of the data could be performed. Two of the major concerns are how to
acr:ount (adjust) for the effect of wind and what to use as the best measure
ment of spray (dependent variable). These considerations are not independent
of one a not her and are app 1 i cab 1 e to a 11 three phases of the study. They w i 1 1
be addressed in section 4.1.1, Study A, although they apply to the phases B
and C as we 11 •
4.1.1 Study A
The primary objective of Study A was to evaluate the five configurations
described in section 3. Before such an evaluation could take place, the two
primary questions concerning how to account for wind effects and what was the
best measure of spray combining information from all possible sensors had to
be addressed. These topics will'be discussed in detail in this section.
Several statistical methods in the form of models were applicable in
assessing treatment effectiveness. Hence, another consideration in this
4-1
analysis was the selectio-n of the best or most informative statistical methods
to be used. Many mode 1 s were ana 1 yzed and wi 11 be brief 1 y described in the
section.
In the proces.s of answering the above questions, ,a procedure or rule was
developed which yielded consistent and logical re~ults for all types of models
considered. This rule involved a definition of tt'e dependent variable (amount
of spray) using 1 inear combinations of only those sensors which were unaffect
ed by the prevai 1 ing winds at the time of the run. This rule is explained
more explicitly in the following section.
ADJUSTMENT FOR WIND EFFECT
The confounding of wind and treatments is the largest potential problem
in the analysis of splash and spray data. Numerous attempts have been made to
adjust for wind effects using statistical covariate models. However, the wind
component is quite complex and no mathematical function combining wind magni
tude and direction adequate 1 y ref 1 ects the camp 1 ex re 1 at i onsh i p between wi nd
and spray. It was thus cone 1 uded that the best approach was one which com
pared treatments under similar or homogeneous wind conditions. This requires
a substantial amount of data collected under conditions which control for wind
as much as possible (e.g. no runs during headwind conditions, etc.). Whereas
this study was conducted in such a manner it was felt that a standard rule or
procedure should be developed which will adjust for wind affects in a less
contra 11 ed environment.
Figure 4.1-1 represents a schematic identifying eight separate wind areas
which produced different splash and spray results for a given treatment condi
tion (excluding headwind conditions). The values along the axes wil 1 be
explained subsequently. Note that no headwind conditions (areas to the right
or north of the truck which is portrayed by the two rectangles in the center)
4-2
c.n <( w c:: < Q z -~
-· + + a. :E 0 (,J In 0 an
I ->
z f
~·
0
0
.•
I I +C"'f I I I I I I I I I I I I I I +G I I I I I I I I I I I I I I +'II' I I I I I I I I I I I
' I I • • • • • • • • • • • + 0 I I I I I I I I I I I I I I +·'II' I I I I
' I I I I I I I I I I +CO I I I I I I I I I I I I I I IC"'f + I I I I I I I I I I I I I I I(&) +-1 I I I I I I I I I I I I I 10 +N I I -------+ -------+ ------•+ + -- I
0
4-3 ID I
tn -
are 1 abe 1 ed s i nee a 11 data co 11 ected under headwind conditions were de 1 eted
from the analysis and, in general, should always be omitted from analyses.
Very few runs were made under headwind conditions in this study. Areas 1-5
represent winds of moderate magnitude (less than 2 mph' and ar~as 6·8
represent stron~ wind conditions. Areas 3 and 7 represent tail winds.
Initially, these wind areas were considered as separate data units and
only data within these units were compared. In the analyses of variance, wind
was regarded as a factor with 8 levels. For example, full treatment runs made
when the wind was stron'g and predominant 1 y from the southeast (area 6} was
paired with data for the no-treatment condition when the wind was a 1 so pre
dominant 1 y from the southeast. Obvious 1 y, there was not a 1 ways sufficient
data in a given wind area for such a comparison. In these cases, wind was
grouped by magnitude (that is, two 1 eve 1 s, strong .. areas 6-8 and moderate -
areas 1-5) or direction (that is, thre·e levels west- are~s 1, 2, 6, south
areas 7, 3 or east - areas 4, 5, 8). These ana 1 yses led to the fi na 1
reconmendation of a method or rule for defining the dependent variable (amount
of spray) as a linear combination of sensors which were minimally affected by
the prevailing wind at the time of the run.
To begin addressing the problem of adjusting for the effect of wind, the
wind speed (WINOSPD), and wind direction (WINDOlR) were transfonned to polar
coordinates by the following mathematical transformation:
X_COMP =- WINDSPO x COS(WINDOIR)
Y_COMP = WINOSPO x SIN(WINOOIR)
The plotting of Y_COMP by X_COMP allows a graphical depictior of the direction
and magnitude of the wind for various test run combinations. These values
comprise the X and Y axis 1 abel s of Figure 4.2-l. F i gure"S 4.1- 2, 4.1-3, and
4.1-4 reflect plots for the data co 11 ecti on in Study A for each truck type
4-4
,. ,.
I
•
•I
•II
to
I
0
.. • 10
. ,.
I
I ! I
I I I J I I • I I
I I ! • I I I I I I • . I
I I I I I • . I I I I I ! • • I I I I I I • ' J .
•
•
Figure 4.1-2 ~MAS& lt·T-UCIC S~LA.W STUOY
~OlAa ~l~T INOICATI•C Wl-0 ·-CIO ••o Ol•&CTI08 , •• OATA STU~' &
• • • • • •
• . .... •
r•vcx• '" ~•
• • . . •
• • . ............ . .•.......•... ...
···················-········································-·-··························---····························-···--
• I • • I
I I I I , . . I
I I I I I ! I I I I I !
.,.
. . t I J I t ! • . J I I I ! . . I I I I ! . i
•••
•
•12 •• .. •
Figure 4.1-3 ~ ..... 11 TRUCK Slt\.ASK STUOV
ltOf.Aa ~1.01' UIOICATIIIG WJIIO S~ICD A.IIO otlUE&:TIQII I'OR ~ATA SefUOY 4
?ave••• .. s•c
•
•
• ... ... • • • • .:::::::o······o···::· ......... . . . . . . . . . .
• • • •
4 • 12
············-····················--·························································•································ • to • t • • t 2 • a • • o a a , t
4-5
,_co ... .. ,.
•
•
••
•••
• ••
i • I
I I I I I I . I
I I I I I I • • I l r I I ! i I I I I • • i I I I . . I
I I I I I • • i .
•
r1gure £f..l-4 --··· tl f-~CX SIJ\~SM S?UOT
........ ,. ... ~ laOtC.AfUC wueo SII,IIO a•o OU.ICTto• -·· o•ra STIIOY a
T•ucx•IM L•c
• • • .. • • • • • • • • • • • • . •......••.... • .. . .. =· · · :.::::::~:o····:·o···::·. . . . . . . . . . . .. . ................ . .. • • • ..•......•...
• • • • • .. • • • • • • • • • •
•
..•. .. ...........•... ·························-········. ······-·········--·-~··············-······································-•20 ••• •tl •• •• • • • 12
4-6
separately. The dotted lines represent the wind areas defined in Figure ~1-
1.
These plots provide a visual diagnostic for assessing the wind conditions
with respect to relevant vari ab 1 es (e.g. treatment and truck type). For
example, from Figure 4.1-2 we note that the wind conditions for all of the COE
runs were predominantly from the southeast and the wind speed was moderate to
ca 1m. For the SNC runs (Figure 4.1-3) the wind was primari 1 y from the south
east and at times quite strong tail winds occurred. The wind conditions for
the LNC runs were somewhat different from either of the other two trucks
(Figure 4.1-4) as the wind direction was uniformly sc·attered from southeast to
southwest and the wind magnitude was re 1 ati ve 1 y 1 ess. As wi 11 be seen in the
result section, there was an inconsistency in the conclusions regarding which
treatment was most effective based on the SNC versus the COE or LNC. These
polar plots indicate that wind conditions were the probable cause for this
inconsistency. -
This technique of partitioning the data by wind condition and examining
the polar plots is especially applicable to situations where wind conditions
cannot be controlled such as field studies. It is reconmended that such plots
routinely be examined in any splash and spray study to determine the extent to
which wind condition may be a factor.
Po 1 ar p 1 ots were produced for each truck and treatment separate 1 y and are
presented in their entirety in the Vol. 2 Statistical Supplement. Additional
plots reflecting the analysis results will be presented in a later section.
In effect, these polar plots provide a visual means of examining wind condi
tions in conjunction with the amount of spray produced and a graphical means
of displaying results. It must be stressed that the location of each point on
these p 1 ots represents the wind speed and direction, not the amount of spray
4-7
produced. The amount of spray can be represented by a coded symbol as wil 1 be
seen in p 1 ots to be presented in Vo 1 ume 2.
SELECTION OF DEPENDENT VARIABLE
Numerous candidates exist for representing the amount of spray produced
for a given run (dependent vari ab 1 e). Pr.evious studies have focused on some
function (geometric or arithmetic mean) of all sensors. This choice of
dependent variable has not been totally satisfying in that measurements during
opposing wind conditions have canceled each other and tended to confound the
effect of the treatments with wind. In this study, several candidate
dependent variables were analyzed. The final selection of the best dependent
v ari ab 1 e was based on a ru 1 e which designated the sensors to be used in the
formulation of the dependent variable based on the prevailing wind condition
at the time of the run.
The camp 1 ete 1 i st of candidate dependent vari ab 1 es considered in this
study follows and the variables are labeled as Rules 1 - 4, respectively.
Rule 1) Sensor 5 - Sensor 8 i nd i vi dua 1 readings. These measurements were found to be highly variable and highly sensitive to wind conditions. Downwind spray readings were quite low and upwind spray readings were high.
Rule 2) Geometric and arithmetic mean of (sensor 5 and sensor 6) or (sensor 7 and sensor 8}. These functions tended to reduce the v ari ab i 1 i ty in the measurements compared to the first candidate; however, the problem of conflicting results from different wind conditions was sti 11 apparent.
Rule 3) Geometric or arithmetic means of all sensors (5, 6, 7, 8). This choice of dependent variable further reduced the variability of the spray measurements; however, the treatment effect was confounded by averaging over all wind conditions. That is, sensor 5 recorded 1 ow when sensor 7 recorded high because the wind was reducing the spray on sensor 7. Averaging these numbers did not truly represent the treatment affect apart from wind. This was being best represented by sensor 5.
4-8
Rule 4) Selection rules. The effect of wind on the sensor readings is obviously quite an important part of the evaluation of treatment effectiveness. A simple linear wind adjustment was unsuccessfully attempted and led to the following suggestion: select as the dependent variable only measurements from those sensors providing the best infonnation on the amount of spray produced by the treatment; i.e .• sensors least affected by the wind condition at the time of the run. The fo 11 owing choices were attempted:
a. If the wind condition is in areas 1, 2, or 6, use the geometric mean of sensors 5 and 6.
If the wind condition is in areas 4, 5, or 8, use the geometric mean of sensors 7 and 8.
If the wind is a tailwind (areas 3 or 7), use the geometric mean of all four sensors.
Figure 4.1-5 depicts this selection rule.
b. Same as rule 4a out use arithmetic mean.
Since the extremely high spray readings generally indicate that the wind
was blowing the spray away from the sensors, another suggestion was to
consider only the lower readings. Thus, Rule 4a was m.odified to select the
minimum value rather than the geometric mean of pertinent sensors. This
choice constituted 4c. A final consideration, 4d, ·was to select the minimum
value among all four sensors regardless of the wind condition. These 1 atter
two suggestions have the disadvantage that they only uti 1 ize one observation
in a given run and thus wi 11 not be as "good" (in a statistical sense). as the
candidates using more observations (4a or 4b).
All of these choices (4a through 4d) further reduced the total vari
ability among the measurements as compared to choices 1 through 3. However,
the variability was still not homogeneous (statistically equal) among treat
ments for a given truck type. This indicates a violation of an inherent
assumption necessary in the analysis of varian~e- namely that the variance of
the popu 1 at ions being compared (treatments) must be equa 1. When this vi o 1 a
t ion occurs, a transformation can sometimes be found which will satisfy this
requirement. In this case, the log transformation did indeed homogenize the
4-9
~ I ._.
0
Figure 4.1-5 PLOT INDICATJNO WIND $PEED AND DIRECTION
RULE 4
Y_COIIP I t5 • WIND AREAS .
tO ... DEPEHDEtiT VARIABLE a
A •
~SEHSOR 5 x.6·---
5 ...
DEPENDENT VARIABLE • ·
0 ~N: ......... . . . 4f- ;~ -~-~-· • • • • • • • • • • . \' ~E~~o~ _s .x. 6. x. 7: .x. o
····TEST· VfHIClE
-5 ...
-to i
DEPEtiDENT VARIABLE .. ~
~SENSOR 7 X 8
-·5 . J
~··---·-·------·-+-·-·--·~~-----+-···-~-----~--·---·--·-----~-·--···--·-·----+--·--·--------·--·----------~-·------------~-·---20 -16 -t2 -a ..... 0 4 8 t2
X_COt.IP
variance. Furthennore, this transfonnation is very intuitively appealing for
the geometric mean since the log of the geometric mean for a set of sensors is
equal to the arithmetic mean of the log of each sensor. Thus, when applying
the 1 og transformation we are mere 1 y consi daring averaging 1 ogs of i ndi vi dua 1
sensors.
The dependent variables described above were re-an~, lyzed using the log
transformation and the selection rules listed in 1 through 4 above. This
report will focus on the results using the log transformation of Rule 4a which
appeared to be best in both a statistical sense and practical sense for
eva 1 uati ng differences among th!! treatments.
STATISTICAL (MODEt.S)
Several types of statistical analyses (or models) wet·e applicable to this
study depending upon the amount of data avai 1 able under various wind condi
tions.
The types of mode 1 s used are described brief 1 y as follows:
a) One-way ANOVAs (one factor, treatment, as the main affect) with data restricted to one area. This was a useful model only if sufficient data were available under a given wind condition. Runs made with truck type SNC provided sufficient data under very restricted wind conditions for this simple one factor analysis..
b) Two-way ANOVA with data restricted to a few wind areas. This model was useful when sufficient data were available from a limited number of wind areas. The two main effects were treatment and wind with the interaction term included in the model.
c) Two-way ANOVA with main effects of treatment and wind direction (left, middle, or right) and their interaction. This was the best available model when insufficient data were available for all wind areas, thus wind was collapsed into only 3 levels reflecting direction. This model was necessary for truck types COE and LNC where there was not enough data in similar wind areas to use models (a) or (b) when comparing a 11 treatments.
d) Two-way ANOVA with main effects of treatment and wind magnitude (high and low). This model was used as an alternative to model (c) to allow for the effect of wind magnitude rather than direction.
4-11
e) One-way ANO VA with treatment main effect over a 1 1 wind cond it; ons. This model was also run in conjunction with (c) and (d). Theresu 1 ts of mode 1 s c. d. and e suggested the u 1 ti mate choice of the dependent variable which will be discussed in the following section.
There was generally very good agreement among the different mode 1 s with
regard to the effectiveness of the splash and spray devices due to the
cantrall ing of wind conditions during this study's runs. It should be noted
that the 1 imited amount of data run during headwind conditions behaved quite
differently from the other areas. Thus, this data was deleted from the
ana 1 ys is and shou 1 d be deleted or regarded separate 1 y in a 11 sp 1 ash and spray
studies.
4.1.2 Study B
This section will discuss the statistical methods (models) used in Study
8. The concerns regarding choice of dependent v ari ab 1 e and effect of wind
were app 1 i cab 1 e to Study S as we 1 1, but wi 11 not be redi scussed in this
section. Study 8 data was ana 1 yzed using the partitioned wind approach and
several dependent variables were considered. However, this report will focus
on analyses based on the recorrmended Rule 4a procedur,e for dependent variable
selection as a function of prevailing wind conditions as discussed in 4.1.1.
The statistical models used were somewhat different in Study B because of the
nature of the study's objective. The primary objective of Study B was to
eva 1 uate the effect of water depth using the base 1 i ne and fu 11-treatment
configurations only. Since water depth is a quantitative variable, this
naturally suggested a 1 east squares regression approach to the prob 1 em where
amount of spray wou 1 d be represented as a function of water depth and a 1 i ne
(or curve) fit to the data for each treatment. A comparison of these 1; nes
(or curves) would address the questions of 1) did the amount of spray increase
4-12
at the same rate with increasing water depth for full-treatment configurations
compared to baseline and 2) was there a significant difference in the average
amount of spray produced by these two configurations at a 11 water depths.
Both a linear and quadratic model were fit to the data in the form of the
equation:
Y = ao + a1 Depth + a2 Oepth2
where Y was the dependent variable using the log transfonnation of "'election
Rule 4a (referred to only as Rule 4 for the remainder of the text). Depth was
the water depth measured at three 1 eve 1 s {.02, .05, and .10 inches) and Oepth2
was the water depth squared. Since there were multiple observations made at
each depth 1 evel for each configuration, a statistical te_st for goodness-of
fit was available inspite of the fact that a quadratic is being fit to only
three di sti net v a 1 ues of the independent v ari ab 1 e. Separate mode 1 s were fit
to each treatment configuration and the model parameters- were then tested for
equi v a 1 ence. If the 1 i near and quadratic parameters were equi v 11 ent, the
curves cou 1 d be considered para 11 e 1. If this was the case but the intercept
terms, a0, differed, then it could be concluded that the amount of spray
produced by one configuration was consistently, significantly greater than the
other configuration at zero water depths. This 1 ast test is not practically
meaningful. If the curves are found to be parallel, then the model omitting
the depth variable should be run to test whether or not there is a difference
in treatments averaged over a 11 water depths.
4.1.3 Study C
The primary objective of Study C was to compare the effectiveness of
splash and spray supression devices for the baseline and NHTSA(4YR) configura
tions on van semi-trailers, tankers, and flatbeds. Since only two configura
tions were compared as opposed to five configurations in Study A, the analysis
of Study C was simi 1 ar to that of Study A but on a reduced sea 1 e. In
addition, the.flatbeds were run in loaded and unloaded conditions. Thus, the
ANOVA model was a two factor model for with interaction (loaded/unloaded and
treatment being the two main affects recorded at two levels each)o Wind, in
general, was not a troublesome variable in that the amount of data available
for the comparisons occurred under similar wind cJnditions for this phase of
the study.
4.2 Results
This section will focus on the results of the analyses for studies A, B,
and c. A summary of the basic conclusions and a recommended procedure for
standardizing the ana 1 ysi s of sp 1 ash and spray data wi 11 be presented in
section 4.3. The reader who is primarily interested in the conclusions rather
than statist i ca 1 deta i 1 s may e 1 ect to bypass sections 4.2.1 - 4.2.3.
4.2.1 Study A
As described in section 4.1.1, many analyses were examined during the
course of this study. These analyses and approaches were all technically
correct, yet conflicting conclusions occasionally resulted regarding treatment
effectiveness. The source of this conflict could generally be traced to the
effect of wi nd. Thus, the authors were 1 ed to the f o 11 owing premi se: it is
imperative that a standardized procedure be developed for analyzing splash and
spray data and that this procedure produce consistent, unbiased results. Such
a procedure has been developed in this study and is summarized in section
4.2.4.
This procedure (Rule 4) involves a selection of the sensors used to
represent the amount of spray for a given treatment which are 1 east affected
by the prevailing wind conditions. This method of selecting the dependent
variable thus reduces the effect of wind as a factor. The statistical method
4-14
variable thus reduces the effect of wind as a factor. The statistical method
hence simplifies to a one-way analysis of variance for evaluating treatment.
A 1 though there is a temptation to present an exhaustive account of a 11 of
the procedures ex ami ned, the authors have e 1 ected to on 1 y report the resu 1 ts
for the recommended procedure. The deta i 1 s of the other ana 1 yses are
documented and available on request.
The first recommended step in examining splash and spray data is an
examination of the polar plots for the truck type (as presented in 4.1,
Figures 4.1.2- 4.1.4) and treatment (Figures AP1- AP19 of Volume 2). These
plots provide a visual means of assessing wind conditions and suggest data
screening procedures (e.g. elimination of all headwind data, etc.) Wind
conditions can be examined for consistency among treatments which is impera
t i ve for justified comparisons. This procedure is es pee i a 11 y recorrmended in
situations where wind conditions cannot be controlled through scheduling {e.g.
in the field}.
Tab 1 es 4.2-1, 4.2-2, and 4.2-3 summarize the number of observations in
each wind area for each truck type in Study A. The numerical designation of
wind area follows that of Figure 4.2-1 with 9 representing headwind condi..t'
tions. To illustrate the danger of ignoring wind in a comparison, consider
setup S(full) and A3(NHTSA(lyr)) for COE, (Table 4.2-l). We see that only 4
points are in similar wind areas. Thus if a difference in treatments was
found ignoring the wind effect, it could not be established whether the
difference was due to the treatments or due to wind affecting the amount of
spray being recorded.
One of the prob 1 ems encountered in the ana 1 ys is of the sensor readings
was a high degree of variabi 1 ity among treatments. This presented a serious
statistical problem in that the statistical method to be used, the analysis of
variance, requires that the variances of the populations being compared
4-15
Table 4.2-l
TRUCK = COE
NUMBER OF RUNS BY WINO AREA AND TREATMENT
1 2 3 4· 5 6 7 8 9 TOTAL
l(BASELINE) 0 3 0 0 l 3 4 l 4 16
2( NHTSA( 4YR)) 0 2 2 l 0 5 4 0 2 16
3(NOAREO NOFSKT) 0 2 2 0 Q. 3 6 1 2 16
4(NO FSKRT) 1 5 .a 1 2 4 0 0 2 15
S(FULLj 0 0 0 0 4 5 6 0 1 16
A3(NHTSA(lYR)) 0 5 2 1 0 3 1 4 0 16
TOTAL 1 17 6 3 7 23 21 6 ll 95
4-16
Table 4.2-2
TRUCK = SNC
NUMBER OF RUNS BY WIND AREA AND TREATMENT
1 2 s· 7 TOTAL
!(BASELINE) 0 4 5 7 16
2(NHTSA(4YR)) 1 3 6 6 16
3(NOAREO NOFSKT) 0 0 13 3 16
4(NO FSKRT) 3 2 11 0 16
S(FULL) 2 1 13 0 16
A3(NHTSA(1YR)) 0 0 15 1 16
TOTAL 6 10 63 17 96
4-17
Table 4.2-3
TRUCK = ·LNC
NUMBER OF RUNS BY WIND AREA AND TREATMENT
1 2 3 4 5 6 7 8 9 TOTAL
l(BASELINE} 4 3 l l 5 1 0 0 1 16
2(NHTSA( 4YR)) 3 0 3 2 2 1 l ~4: 0 16
3(NOAREO NOFSKT) 1 3 0 0 5 1 l 4 l 16
4(NO FSKRT) 3 3 3 1 i 0 2 1 2 16
S(FULL) 5 5 0 0 3 0 l 0 2 16
A3(NHTSA(lYR)) 2 3 3 0 4 2 1 1 0 16
lA 2 2 0 0 0 0 0 0 1 5
TOTAL 20 19 10 4 20 5 6 11 7 101
4-18
(treatments) be equal. Table 4.2.4 lists the sample size, mean, and variance
for each sensor reading, the geometric mean of all four sensors, and the
dependent variable defined as the 1 og of the geometric mean of only those
sensors not affected by the prevai 1 ing wind conditions at the time of the run
(RULE4). Note that for the LNC, the geometric mean of all four sensors
resulted in a variability of 12.4 for the no aero, no skirt treatment (3} and
203.2 for full treatment (5). The general rule is that the variances should
not exceed a fourfold difference in magnitude among treatments. The vari
ability of the RULE4 variable was generally within these limits. This follows
intuitively, in that the restricted choice of sensors in RULE4 resulted in the
elimination of sensor readings highly affected by wind thus dec~easing the .
variability. However, the log transformation was necessary to further reduce
the variability within acceptable limits. This transformation is also intui
tive in that responses which reflect percentages often require a 1 og trans
formation to satisfy the normality assumption. Note: although not presented
here, the log transformation of each sensor and the 1 og transformation of both
the geometric and arithmetic mean were ex ami ned and did not adequate 1 y reso 1 ve
the heterogeneity of variance problem.
The one-way analysis of variance results using RULE4 as the dependent
variable are listed in Table 4.2-5 by truck type. The number of observations
and mode 1 root mean squared error (-{'MSE) are 1 isted a 1 ong with the over a 11 F
statistic and p-value {the significance level at which the test of equality
among a 11 treatment means wou 1 d be accepted). A p-va 1 ue of 1 ess than .05
means that at least one treatment mean differs from the others at the
generally accepted five percent level of significance. This overall F-test
was always significant hence a Duncan's multiple range test was conducted to
determine which treatments differed.
4-19
~ I
N 0
TRUCK SETUP OF TRUCK
-COE t(BASE-
LINE)
2(NHTS-A(4YR))
3(NOAR-EO NOFSKT)
4(NO fSKRT)
5(fUll)
A3(NHT-SA(tYR-))
SNC a( BASE-LINE)
2(NHTS-A(4VR))
3(NOAR-EO NOFSKT)
4(NO FSKRT) ---5(FUll)
A3(NHT-SA(1VR-))
·--·--- -----· lNC t(BASE-
liNE) ------· 2(NtHS-A(4VR))
------ ···----
(CONTINUED)
SENSORS I
N MEAN VAR
12 36.77 362.664
t4 49.41 567.950
14 44.78 459.488
13 59.18 324.716
15 75.74 373.245
16 57.85 788.461
16 28. 14 158.263
16 42.55 171.232
16 42.06 272.463
16 38.07 324.743 f- ---- ----16 33.71 198.589
---·
t6 33.49 76. 183 - --- ,__, ___ 15 63.24 1064.29 -·- --- ----
16 62.99 586.421 ---- --------
Table 4.2-4 SUMMARY STATISTICS FOR STUOV A .
SENSOR& SENSOR7 SENSOR I
MfAN VAR MEAN VAR MEAN VAR
16.50 69.675 25.12 846.186 61.57 1479.33
29.47 381.068 25.32 239.856 52.05 642.349
2 t. 19 184.872 t7.72 37.511 43.56 361.589
29.70 344.815 64.29 546.784 88.22 1ot5.602
51.09 642.191 45.02 1039.35 68.72 949.102
33.71 656.568 2t. 71 395.514 47.51 906.849
7.46 16. 121 57.39 984.775 89.19 152.487
26.07 39.813 69.10 567.780 92.36 142. 147
24.52 107.043 71.81 595.831 89.12 275.338
15.11 54.870 89.20 38.788 95.19 17.785 ·--13. 16 14.289 88.12 55.109 95.41 11.200 _ _______,.., --- r---·.
16. 12 19.9 t 1 77.36 355.368 93.92 44.873 --·~·- ··---·
34.46 747. 161 23.65 596.846 47.73 1242. 11 ----· ·----- ----- ·-
36.78 287.884 25.11 224. 123 47.35 903.264
GEOMETRIC MEAN Bf
' 5,6,7&8 L.\IRUlE4
NfAN VAR MEAN VAR
' 26.79 190.607 2.83 0.297
34.47 131. 167 3.40 o. 123
27.81 8t.650 3.28 0. t24
51.86 71.907 3.52 0.228
50.65 215.957 3.49 0.537
31.50 75.507 3.09 0 .• 149
28.81 55.704 2.83 0.434
49.93 24.546 3.58 0.107
47.96 21.903 3.41 0.067
45.49 9t.090 3.07 0.179
43.12 47.;676 2.99 0.106 -- ---H·--------
43.46 21.535 3. 14 0.096 ·---· ---·--. -··
28.22 .29. 433 2.65 0.528 --- ----· ·---- -----·
35.98 31.260 3. 18 0.226 . ·-------- ·---·· ····------- -----· ·---· ·--- ----·---- ----------····
~ I
N .....
TRUCK
lNC
~-~--
SETUP OF TRUCK
3(NOAR-EO NOFSKT)
4(NO FSKRT)
5(FULL)
A3(NHT-SA(1VR-) )
tA ----
SENSOR5
N MEAN VAR
15 72.26 692.408
14 85.08 78.122
14 74.26 367.001
16 56.02 791.300
4 73.65 313.097 '----- ------- ~-----------
Table 4.2-4 Continued SUMMARY STATISTICS FOR STUDY A
SENSORG SENSOR7 SENSORS
MEAN VAR MEAN VAR MEAN VAR
45.40 761.664 23.52 248.005 38.52 560.597
54.21 372.291 51.88 705.582 77.14 639.724
49.59 532.787 61.46 966.055 80.81 566.362
29.31 397. 167 24.84 239.296 57.61 935.463
39.82 466.109 68.02 180.729 90.35 56.363 ----~---- ------~----- ---------- -------· ~- ~.
•...
GEOMETRIC MEAN OF 5,6,7&8 LNRULE4
MEAN VAR MEAN VAR .
35.98 12.439 3.11 0.187
60.71 215.835 3.80 0.563
59.06 203. 191 3.66 0.406
33.47 12.464 3.10 0.143
62.25 161.622 3.87 0.335 .. - -·
Table 4.2-5
Sunncry For Stl.Xiy A
Culcan's Trtek febltiple T,Yt:e n r.& F-statistic P-value Rang! Test Expected Differe1ee in Se'lsor Readings
tDE 84 .493 3.79 .004 coni(Expected all.e) 1 :A 3 2 4 5
S( 42.9) 23.8 19.1 14.8 u.o 4.9 0
4( 38.0) 18.9 14.2 9.9 6.1 0
2(31..9) 12.8 8.1 3.8 0
3(28.1) 9.0 4.3 0
3A(23.S) 4.7 0
1(19.1) 0
Si! 9S .at! 7.39 .dlJI cii1d (EXi5i$d valt.e) 1 5 4 3A 3 2
2(29.4) 19.4 10.0 8.1 6.7 1.3 0
3(28.1) 18.1 8.7 6.8 5.4 0
~(Zl. 7) 12.7 3.3 1.4 0
4(21.3) 11.3 1.9 0
5(19.4) 9.4 0
1(10.0) 0
lNC 9l .619 5.74 .alE cord (Expected vallS) 1 3(\ 3 2 5 4
4{59.0) 40.6 35.2 34.4 32.1 11.5 0
5( 47 .5) 29.1 23.7 22.9 20.6 0
2(26.9) 8.5 3.1 2.3 0
3(24.6) 6.2 0.8 0
3ll.(23.8) 5.4 0
1(18.4) 0
4-22
The mean for each of the treatments (conditions) is listed in Table 4.2-5
along with the multiple range results. Vertical lines denote treatments which
were equal. For the COE truck, full treatment (5) was significantly better
than no treatment (1) since the average percent of 1 ight passing through the
sensors for full treatment {42.9) was significantly higher than the average
percent of light for the no treatment condition (19.1). However, there was no
significant difference in spray reduction among the other treatments compared
to full treatment. The results for the SNC truck were somewhat different in
that the no treatment condition, though 1 east effect i ve among the five treat
ments was not significantly worse than full treatment. In fact, none of the
treatment combinations could be- singled out as significantly better or worse
than the others as evidenced by the overlapping vertical lines. The LNC truck
produced results similar to the COE in that the no treatment condition was
significantly less effective than the aero~id treatments_ {4 and 5).
The remaining columns in Table 4.2-5 denote differences among the
estimated expected spray for a given treatment compared to each of the other
treatments. For example, for the COE truck, full treatment can be expected to
yield, on the average, 42.9 percent 1 i ght transmittance, whi 1 e treatment 1 (no
treatment) will only yield, on the averge, 19.1 percent 1 ight transmittance.
Thus, full treatment will yield an increase of 23.8 percent light trans
mittance over no treatment (column labeled 1). Full treatment will only yield
a 4.9 percent increase over condition 4 (column labeled 4). The larger the
va 1 ues in these co 1 umns, the greater the effect of one treatment over another
in reducing spray (increased 1 i ght transmittance).
Tne estimated mean sensor readings reported in Table 4.2-5 are also
depicted graphically in Figures 4.2-1- 4.2-3 in order of decr-easing
effectiveness (the higher the bar the more effective the treatment in reducing
spray). Again, note that whereas the no treatm.ent condition is always the
4-23
• • • • • • ... • • • • ... • • . • • • • • • • • • • • • • • • • • .. . • • • ... • • + + • ... + + • • • ... • • • • + • + • + + + • • • • .. • • • • . • + • + • • + + ... • • • + • • • . • .. • • • .
I I .. .. + • • • • • • • • • • • • • • • • + • + • • I
ex • • • • • • • + • + • • + • • • • • • • • • • • I< Q • • • + + • • • + • • • • + • • • • • + • • • • :(¥) "" • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • .. • • • • • .. • • • • • • I
"' I Q. I
= ' ... I ..., I
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ii • • • • • • • • • • • • • • • • • • • • • • • • • • • • I M • .. • • • • • • • • • • • • • • • • • • • • • • • • • • I ...... • • • • • • • • • • • • • • • • • • • • • • • • • • • •
"' ... z ,..... :J: z c
I .,..., ..., NCexi.U 2
...... ..., Q Q ~Q."-<.J ""' z
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cu~;! • • • • • • • • • • • • • • • • • • ... • • • • • • • • • • • • • (J ... • • • • • • • • • • • • • • • • • • • • • • • • • • • • • ... • • ("f ~(,J ... ex • • • • • • • • • • • • • • • • • ... • • • • • • • • • • ... • • • ::S!:)I.U(,J ! • • • • • • • • • • • • • • • • • • • • • • • • ... • • • • • • • c:::na::c ......... ex (,J
~.~.. ... ex ... ex -c c ... m ..., (I) (I) • • • • • • • • • • • • • • • • • • ... • • • • • • • • • • • • • • • • • • • ~z • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • -· • • • • • • • • • • • • • • • • • • • • • • • • "" • • • • • • • • • • • • • • Q."' • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • 2 • • • • • • • • • • • • • • • • • ... • • • • • • • • • • • • • • • • • • • •
Q
"' ... c 2 -... • • • • • ... ... • • • • • • • • ... ... • • • • • • • • • • • • • • • • • • ... • • • • • • • en • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • ... • • • "' * ... • • • • • • • • * • * • * • • • • • • • • • • • • • • + + • + + • • • • • * • • • In
• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • * • • • • • • • • • • • • • • ... • • • • • • • • • • • • • • • • • • • •
z c Q "' ... 2
-·----·----·----·----·----·----·----·----~ g ~ ~ ~ g ~
4-24
Figure 4.2-2 PHASE II TRUCK SPLASH STUDV
ESTIMATED MEANS FOR THE DIFFERENT TRUCK SETUPS FOR TRACTOR•SNC
BAR CHART Of MEAN
MEAN
I ••••• ••••• ••••• • ••••
27 ... • •••• • ••••
I ••••• • •••• ••••• • •••• ••••• • ••••
24 + ••••• • ••••
I ••••• • •••• ••••• • •••• • •••• ••••• • •••• • •••• 21 + ••••• •••••• ••••• •••••
I ••••• • •••• • •••• • •••• ••••• • •••• • •••• ••••• • •••• ••••• ••••• ••••• • •••• • •••• 18 ... ••••• • •••• • •••• • •••• • ••••
I ••••• ••••• • •••• ••••• • •••• ••••• ••••• ••••• • •••• • •••• ••••• • •••• ••••• • •••• • •••• t5 ... ••••• ••••• • •••• • •••• • ••••
~
I ••••• ••••• ••••• • •••• • •••• I N ••••• ••••• • •••• • •••• • •••• (J1 ••••• ••••• ••••• • •••• • ••••
12 ... ••••• • •••• • •••• • •••• •••••
I ••••• • •••• • •••• ••••• • •••• ••••• • •••• • •••• ••••• • •••• ••••• ••••• • •••• • •••• • •••• • ••••
9 ... ••••• ••••• ••••• • •••• • •••• • ••••
I ••••• • •••• • •••• ••••• • •••• • •••• ••••• ••••• • •••• ••••• • •••• • •••• ••••• • •••• ••••• • •••• ...... • •••• 6 + ••••• . ..... • •••• • •••• • •••• • ••••
I ••••• ••••• ••••• • •••• • •••• • •••• ...... ••••• ••••• . ..... .. .... • •••• ••••• • •••• ••••• ••••• • •••• • •••• 3 ... ••••• ••••• • •••• ••••• ••••• • ••••
I ••••• ••••• ••••• ••••• • •••• • •••• ••••• ••••• • •••• • •••• • •••• • •••• ••••• ••••• • •••• ••••• • •••• • ••••
-------------------------------------------------------------------------2 3 3A 4 5
COND
Figure 4.2-3 PHASE II TRUCK SPLASH STUDY
ESTIMATED MEANS FOR THE DIFFERENT TRUCK SETUPS FOR TRACTOR:LNC
BAR CHART OF MEAN
MEAN
60 + ***** ••••• ***** ***** *****
50 + ***** ***"'* ***** ***** ***** ****"' ***** ***** *****
40 + ***** ***** ***** ***** ****"' ••••• ***** ***** ***** *****
30 + ***** ***** ***** ••••• ••••• • •••• • •••• ••••• ***** ***** ***** ***** ***** ***** ***** ***** *****
20 + ....... ***** ***** ••••• • •••• ...... .. .... . ..... ***** ••••• • •••• ••••• ***** ••••• • •••• ***** ••••• ••••• ***** ••••• ***** ••••• ***** ...... ***** ***** ***** ***** ***** 10 + ••••• • •••• • •••• • •••• • •••• ***** ••••• . .... ,.,. • •••• . ...... ***** ••••• ••••• ***** ***** ••••• .. ...... *****
••••• . ...... • •••• ••••• . ...... ***** ••••• • •••• • •••• ••••• • •••• • •••• 4 5 2 3 3A
COND
worst case as it occupies the 1 ast position on these charts, there is dis
agreement as to which treatment is distinctly best among the three truck
types. The aeroaid treatments do appear to be very effective in reducing
spray based on the COE and LNC results.
The analysis of variance tables for these runs appear in Volume 2.. Two
items should be noted: 1) The analysis of variance results for the LNC were
done with and without treatment lA but Tab 1 e 4.2-5 ami ts this treatment, 2)
The resu 1 ts of the Duncans ana 1 yses do not rank order treatments in the
exact 1 y the same order as reported in Tab 1 e 4.2-5 s i nee the estimated
variances in the back transformation differed. This is explained further in
Volume 2.
4.2.2 Study 8
The results for this study will be presented based on the selection rule
for sensor readings which adjusts for the effect of wind~ The main ob.iecti ve
of this study is to eva 1 uate the effect of no treatment compared to the F u l 1
treatment at three different water depths. Since the effect of wind was
incorporated in the se 1 ecti on of the dependent vari ab 1 e, a quadratic
regression model in terms of water depth alone was sufficient for describing
the relationship of water depth to spray production for the two treatments
over all wind conditions. This method is described in detail in 4.1.
Again, the first step was to examine the polar plots of wind cond;tion
for the two treatments at each water depth to ensure that fairly unifonn wind
conditions exist among these runs. These plots can be found in Figures AP20 -
AP25 of Volume 2. With the exception of a few headwind conditions which were
omitted from the analysis, wind conditions were reasonably uniform throughout
this phase of the study.
4-26
Tab 1 e 4.2-6 1 i sts the s amp 1 e size, mean percentage readings, and
variances for each sensor, the geometric mean of a 11 sensors, and the
selection rule, RULE4. Note that whereas the variances among these treatment
groups were more uniform than in Study A, the se 1 ecti on ru 1 e did reduce the
variability considerably.
Regression models were fit to each treatment and the results are
summarized in Table 4.2-7. The R2 values for these models are not extremely
high indicating that these models should not be used in a predictive sense
(e.g. one should not attempt to extrapolate the amount of spray which would be
produced at a water depth of .08). The asterisks indicate that the model
parameter is statistically different from zero at the .OS 1 evel of
significance. Thus, for the base configuration (no treatment) the intercept
and linear terms were significantly different from zero but the quadratic term
{amount of curvature) was not. For full treatment, the intercept term was
different from zero but the other terms were not. The ..J MSE's were near 1 y
equal indicating similar error variability in the two models. The latter is a
necessary requirement for the next step, testing the equa 1 i ty of the two
models.
Figure 4.2-4 is a p 1 ot of the expected v a 1 ues for each treatment at each
water depth. These v a 1 ues are 1 i sted in Tab 1 e 4.2-8. Note that a 1 though the
improvement of full treatment over baseline is uniform at all depths, it is
not as great under deeper water conditions.
The regression analysis for testing the equality of the two models is
presented in Table 4.2-9 and sunmarized in Table 4.2-10. The curves for Base
and Full treatment were statistically compared by fitting a re9ression model
with indicator variables. The T-values for the model terms Zl, Z2, and Z3
test the equality of intercepts, linear terms, and quadratic terms for the two
curves, respectively. Since the p-values are greater than .OS for Zl, Z2, and
4-27
.J::lo I
N (X)
-WAlDE-PTH
SHALL-ow
MEDIUM
DEEP
SETUP Of TRUCK
1(BASE-LINE)
5(FULL)
1(8ASE-LINE)
5(FULL)
1(8ASE-LINE)
5(FULL)
SENSOR5
N MEAN VAR
16 78.04 431.348
16 9t. 19 60.211
t2 36.77 362.664
15 75.74 373.245
t6 68.59 443.344
16 75.50 210.983
Table 4.2-6 SUMMARY STATISTICS FOR STUDY 8
G,EOMETRIC MEAN Of
SENSOR& SENSOR7 SENSORS 5,6,7&8 LNRULE4 '
MEAN VAR MEAN VAR MEAN VAR MEAN VAR MEAN VAR
48.48 1080.28 23.74 327.037 40.16 476.624 40.68 376.489 3.54 0.271
79.78 290.572 40.36 518.001 67.72 453.551 63.69 181.567 4.03 0.203
t6.50 69.675 25. t2 846. 186 6t.57 1479.33 26.79 190.607 2.83 0.297
5t.09 642. tat 45.02 1039.35 68.72 949. t02 50.65 215.957 3.49 0.537
35.26 541.379 8.39 15.809 2t .34 55.22t 24.07 80.689 2.97 0.233
56.46 410.021 27.47 1246.61 47. t2 tt 10.35 38.28 229.377 3.04 0.627 .. -~
Condition n
Base 44
Full 41
Table 4.2-7
Regression Analysis Sumnary Separate Models Fit to Base and Full
Model: RULE4 = ao + a1 (DEPTH) + a2 (Oepth) 2
MSE
.514
.674
ao
4.34 (12~98)*
4.50 (10.6)*
Parameter Estimates {T-values)
al a2
-46.6 329.2 (-3.2)* {2.8)
-25.8 112.00 {-1.45) {0.8)
4-29
R2 F
.28 7.87
.28 8.56
MEAN I 75 +
I 70 +
I 65 +
I 60 +
I 55 +
I ~ 60 i
45 +
I 40 +
I 35 +
I 30 +
I 25 +
I 20 +
I
fiGURE 4.2-4 PLOT Of EXPECTED VAlUES
FOR BASE AND FULL TREATMENTS
PLOT OF MEAN*DEPTH SYMBOL IS VALUE OF COND
---+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+--0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 O.tt
D£PTH
Table 4.2-8
Model Expected Values
Water Depth Base Full Improvement
Shallow (.02) 46.57 76.02 29.45
Medium (.OS) 22.90 44.30 21.40
Deep (.10) 26.34 28.25 1.91
Over a 1'1 31.19 45.68 14.50
4-31
Table 4.2-9 Regression Analysis Comparing Base and Full T~eatment Curves
Model: RULE 4 = a0 + a1 Depth+ a 2 Depth 2 + a3 z1 + a4 z 2 + a5 z5
~MASI It T•UCX S~\ASM STVOY OUAOaATIC fi'IT o• OI~TM WITM co•o AMO t•TiaACTta• t•OtCATOaS
.... Y4aU~OLC: .. ......... ...... . .. ... ..
souaca ... ••••••• •••••• , YAUtl .. ... , .. ....... • tt.IA.JOO:I ~ ....... .. ·" ..... , ••••• •• ~·······:. ·-~·~··· c TO'I'AL •• • •••• 21!1'7
IJOOT ... •• IOIOSO •·•ouaac 0.:1:110 .. ,. ..... :1.~!1'?170 ao"' • ••• .. , ... C.Y. ...... ,.
~ ..... , .. sTaoo••• T fi'Oa MO: Y&ataaLI YAOIAOI.C Ill' ISTIMATI ••••• - ....... , ••• 0 -•a• ) lTl ~. ...... ,., •• c ... ..... ., . ., .. ,.,.,., .. 11.101 ...... t•'twaca .... , .. •18.7110.22 1S.&t!IOS• ., . ·~· o. tO'f1 .... , ... 0. ,,,_ . ., . 111.141 o .•••
·-~"·· z, •0.11'72:1. O.S44tal •o.:za• • • .,.,21 t:l ..... .,.,.,.:. t:l,ltiSU •o.••• o.:l'fto u "". , . ., .... ,,. '.te:a o.aaat
4-32
Terms
Intercepts
Linear
Quadratic
Table 4.2-10
Results of Comparison Base vs Full
Average overall Depths
4-33
T-values
-.289
-.899
1.163
2.76
Z3, this means the curves are parallel and differ by a constant amount. To
test the equality of spray averaged over all depths, a one-factor ANOVA model
(T-test) was run and the result was not significant (T=2.76). Thus, the full
treatment is not significantly more effective than the base treatment ov.er a 11
water depths.
The data for this study provide an excellent example of the uti 1 ity of
RULE4. Figure 4.2-5 reflects the average sensor readings for each sensor for
the baseline and full treatments. The high d.egree of variabi 1 ity (noise)
among sensors is due to the wind affect which is adjusted for using Rule 4
(Figure 4.2-4).
4.~.3 Study C
The fundamental question to be addressed in this phase of the study was,
is there is a difference between the NHTSA-4 year rule and full treatment for
van semi-trai 1 ers, tankers, and flatbeds? In addition, these treatments were
compared for flatbeds under both 1 oaded and un 1 oaded conditions. The resu 1 ts
of this study will be based only on selection RULE 4 although many analys~s
and models were run as described in Section 4.1.
The results will be reported for each truck type. Table 4.2-11 lists the
nwnber of runs in each wind ar.ea for each treatment and truck configuration.
Polar plots of the wind conditions are presented in the Appendix of Volume 2.
Table 4.2-12 presents the summary statistics of means and variances for the
geometric mean of all sensors and RULE 4. Not.e that even application of RULE
4 did not correct for the extreme differences in variabl ity for the 1 oa.cfed
flatbed. The reason for the extreme 1 ow vari abi 1 ity for the NHTSA 4-year ru 1 e
and high variablity for the baseline treatment cannot be e)(plained. Wind
conditions were simi 1 ar. 'Because of this non-nomogene i ty of v ar i an<:e, a 1 1
comparisons involving the loaded SNC van are questionable.Table 4.2-13 presents
the summary of mean differences in tr.eatments for Study C.
4-34
,. It
• D I c T I D
y A L u I
10
'70
10
so
40
20
20
I
! + I I I I I +
i I I I + I
I I ! +
i I ! +
l t ! + I
I I ! +
i I I I
10 + I
I I !
0 + I I
Fj gure 4. 2-5 Plots of Sensor Means
~~OT P~OT Pt.OT lli.OT
,HASI II TRUCK ~~~ASH STUDY OUAORATIC RIGRISSION ON WATIR DI~TH
STUDY I SITU, 0~ TRUCK•1IIASILINII
0" PS•OI'TH SYMIOL USED JS I 0~ PI•DI~TH SYMIOL USID JS I
a" P"I•DI~TH SYMIOL USID IS '7 OP lli•OIIJTN SYMIDL USID IS •
··················•·························•············•·······-·--··········-·························-·-··········-···•···· 0.01 0.02 0.03 o.o .. o.os o.os 0.0'7 0.01 0.01 o. 10
NOTI: tlol DIS HIDOCN
,. It I 0 I c T I D
v A L u I!
10 l l I
'70 1
10
l I ! so +
oiO
i I
20 l i I I I
20 +
10
i I !
0 + I .
,.HASI U TRUCK SPLASH STUDY OUAORAfJC RlllRISSION ON WATCA DCPTH
STUDY I SITUP Of' TIUICIC •S C f'UU, I
PLOT 0~ Pt•OIPTH PLOT 0~ ~S•OI~TH PLOT Of' ~T•OII'TH PLOT Of' ~S•OC~TH
SYM110L USID IS I SYMIOL USIO JS I SYMIOL USCD lS 7 SYMIOL USCD IS I
••o••+••••o••••••••••••••••••••+•••••••••••••••••••~•••••+••••••••o•••+••••••••••••+••••••••••••+••••••••••••+•••••••••••••••••
0.01 0.02 0.02 O.Ool 0.01 0.01 0.0'7 0.01 o.ot o. 10
DIEPTH
Table 4.2-11
NUMBER OF RUNS BY WINO AREA, TRUCK, AND TREATMENT
1 2 3 4 5 6 7 8 9 Tot a 1
LNC TANKER 8asel 1 ne 0 2 3 3 0 0 6 2 0 16 NHTSA{4YR) 1 1 2 0 3 3 2 4 0 16
TOTAL 1 3 5 3 3 3 8 6 0 32
. SNC FLATBED UNLOADED
Baseline 10 4 1 0 0 1 0 0 0 16 NHTSA(4YR) 15 0 1 0 0 0 0 0 0 16
TOTAL 25 4 2 0 0 1 0 0 0 32
SNC FLATBED LOADED
Baseline 3 2 0 0 0 9 2 0 0 16 NHTSA(4YR) 3 3 0 0 0 10 0 0 0 16
TOTAL 6 5 0 0 0 19 2 0 0 32
Baseline 5 5 0 0 0 5 1 0 0 16 FULL 4 0 0 0 0 11 1 0 0 1•6
TOTAL 9 5 0 0 0 16 2 0 0 32
4-36
TRUCK
LNC + TANK
. SNC FB UNL
SNC FB LOO
.. COE 2 VAN
Table 4.2-12 SUMMARY STATISTICS FOR STUOY C
GEOMETRIC MEAN OF 5,6,7&8 LNRULE4
N MEAN VAR MEAN VAR
SETUP OF TRUCK
1(BASELI-NE) 16 46.26 25.756 3.70 0.132
2(NHTSA(--4VR)) 16 -48.69 36.3!58 3.-49 0.154
1(BASELI-NE) 16 62.67 51.608 3.76 0.098
2(NHTSA(-4YR)) 16 62.43 36.522 3.73 0.076
1(BASELI- !
NE) 16 42.50 148.80!5 2.94 0.830
2(NHTSA(-4YR)) 16 57.21 1·3.940 3.!59 0.017
1(BASEL1-HE) 16 32.78 63.864 2.79 0.465
'5 16 43.92 182.004 3.03 0.672 _j
4-37
Table 4.2-13 Sunrnary of Mean Difference in Tr.eatments
Truck Type n MSE NHTSA( 4YR)* Baseline Difference
LNC TANKER 32 .242 35.41 43.21 -7.8
SNC UNLOADED 25 .247 43.29 45.10 -.l.SO
SNC LOADED 32 .671 36.54 28.65 7.89
COE 2 VAN* 32 .754 28.96 20.54 8 .. 42
* Full Treatment for COE
4-38
The NHTSA 4-year rule was no more effective in reducing splash and spray
over baseline (no) treatment for any truck types. Analysis of variance tables
for these runs can be found in the Appendix of Volume 2.
4.2 •. 4 Sunmary
Procedure for Analysing Splash and Spray Studies
Due to potential confounding of treatment effect and wind effect, it is
reconmended that a standard procedure be accepted for the analysis of splash
and spray studies. A recommended procedure which evolved from extensive
examination of numerous candidate methods {4.1.1) is described in the
following:
Step 1: Examine polar plots of the wind conditions existing during each run of the study by the various factors to be compared in the analysis (e.g. truck type and treatment).
Step 2: Examine frequencies of the number ·of runs available for comparison for each wind area and factor (truck/treatment) combination. If the number of runs available for comparisons differ dramatically among wind areas, the selection Rule 4 must be invoked and is the only method which has the potential for evaluating treatments unconfounded by wind.
Step 3: If wind conditions are highly variable, invoke the following rule for defining the best measure of splash and spray which will be minimally affected by wind conditions (Figure 4.1-5):
• If the wind condition is in area 1, 2, or 6, use the geometric mean of sensors 5 and 6 (downwind sensors).
• If the wind condition is in areas 4, 5, or 8, use the geometric mean of sensors 7 and 8 (downwind sensors).
• If the wind is a tailwind (areas 3 and 7) use the geometric mean of all sensors.
• If the wind is a headwind, omit data or analyze separately.
Step 4: Examine means and variances for a 11 dependent v a·ri ab l·es being considered for analysis by factor (truck/treatment) combinations to be compared. That is, the arithmetic or geometric mean of all sensors may be a suitable measure of splash and spray, provided wind conditions were not too disparate. However, if the variabi 1 ity of these means differ by a factor of more than four among truck/treat-
4-39
ment combinations, the homogeneity of variance requirement for the analysis of variance is in violation and a transformation may be necassary ..
Step 5: If a transformation (e.g. log) is nec.essary, re-examine means and variances of the transfonned variable to ensur.e that the homogeneity requirement has been satisfied.
Step 6: Perform analysis of variance and draw·conclusions. Not.e: If the log transformation has been used, the back .;ransformation of the expected values must tl done using both the mean and variance of the log transformed value (Volume 2).
Stud¥ A Results
Following the above steps, RULE 4 was used to evaluate the effectiveness
of five configurations on three truck types with the following conclusions by
truck type:
COE: Full treatment significantly reduced the amount of spray produced over no treatment allowing an average of 23.8 percent more light to pass through the 1 asers. There was no significant improvement in the full treatment over treatments 2, 3, and 4.
SNC: Full treatment did not signficantly reduce the amount of spray produced over any of the other treatments. However, treatment 2 resulted in significantly more light passing through the laser than treatments 4, full, or no treatment by 19.4 perc.ent.
LNC: ·Full treatment and treatment 4 significantly reduced splash and spray over no treatment a 11 owing 29.1 and 40.6 percent more 1 i ght to pass through the lasers, respectively.
Overall: Treatments with aeroaid generally resulted in significant splash and spray reductions. The no treatment conf i"gur at ion a l ways res u l ted i n the lowest percentage of 1 ight passing through the 1 asers. The SNC conclusions were not consistent with the COE and LNC results. However, wind cond it i or.~ for the SNC were more varied and gr.e ater in magnitude than for the COE or LNC (Figures 4.2-2, 4.2-3, and 4.2-4). Also, the maximum reduction among treatments in the percent of light passing through the 1 asers was 1 ess (19.4) for the SNC than the COE (23.8) or the LNC ( 40.6).
Study 8 Results
·Full treatment is not significantly more .effective than no treatment in
r.educi ng spray over a 11 threo. water depths test.ed (.02, .OS, and .10). At the
de.epest wat.er <lepth, the amount of improvement was minima 1. Both treatments
exhibited the same relationship in the amount of spray reduced as a function
4-40
of water depth, i.e. as water depth increased the amount of light passing
through the 1 asers decreased quadrati ca 11 y for both base and fu 11 treatments.
Study C Results
The NHTSA-4year rules did not result in significant improvement in the
reduction of splash and spray for the LNC-tanker, SNC flatbed (loaded or
unloaded) or the COE van.
4-41
4.3 Chase Car Results
Chase car data tapes from representative runs identified in Tabl.e
4.3-1 were reduced using the following approach. Since the velocity of
the chase vehicle and its location with respect to the test vehicle were
known, a point, at which the on-board lasP ... transmissometer could be
assumed to be affected by the spray th«2t was also being measured by
fixed lasers 5 and 6, could be estimated. Then the level of transmission
for each cycle of the windshield wipers as measured by·the
transmissometer was measured by reference to the calibrati~n trace that
preceded each run. Arbitrarily, it was decided to add the transmission
levels for ten seconds, taking as the level for each ten-second interval
the minimum light level recorded, and then to take the arithmetic
average of these ten observations as an indicant of light transmission
through the cloud of spray that was simultaneously being measured by
lasers 5 and '6 and being looked through to the test vehicle by the chase
car observers.
The entire test pass took 17 secon<.is on each run. It thus made
sense to measure how long the target vehicle was in view as recorded by
the cha·se car observers, and get a figure of merit by dividing time on
target in seconds by 17. Then these two target visible scores were
averaged to arrive at a final score for correlation.
Table 4.3-1 provides the derived data from which a correlation
analysis was done. This table gives the vehicle tractor (all A study
data) , spray suppr.essant condition ( 1, 2, or 5), the g.eometri c mean of
1 as.ers 5 and 6 on that run (convert-ed to et deci rna l), the mean 1 aser
per<:ent transmis·sion, and the target visibility score. Certain runs were
e 1 i mi nated for the ana 1 ys is even though they wer-e reduced, because the
4-42
TABLE 4.3-1 COMPILATION OF CHASE CAR MEASUREMENTS
VEHICLE CONDITION RUN NO. GEOM LASER VISIBILITY IH COE 5 49 0.681126 79.5 0.4710
50 0.175955 75.0 0.4415 51 0.726004 81.5 0.5000 52 0.833313 82.5 0.5000 53 0.404533 81.5 0.4560 54 0.229135 79.0 0.3530
IH COE 2 55 0.233345 70.0 0.3330 56 0.286496 78.8 0.4265 57 0.345919 83.0 0.4410 58 0.348419 76.5 0.4410 59 0.283284 63.5 0.4850 60 0.261098 76.0 0.2645
IH COE 1 61 0.244753 65.6 0.3090 62 0.182266 64.2 0.2950 63 0.229617 68.5 0.2500 64 0.274401 71.3 0.2795 65 0.208178 68.0 0.2205 66 0.321439 70.0 0.2940
IH COE 5 72 0.414415 75.0 0.4265 73 0.786944 87.0 0.4560 74 0.468081 74.5 0.4415 75 0.529240 87.5 0.3530 76 0.606426 87.0 0.3970
IH COE 2 77 0.503249 74.5 0.4265 78 0.796188 74.0 0.5000 79 0.296923 68.0 0.3385 80 0.766720 78.5 0.3970 81 0.379241 69.0 0.3970
IH COE 1 97 0.182932 66.5 0.2795 98 0.302742 73.5 0.2645 99 0.182052 71.0 0.2645
100 0.110887 57.0 0.2355 101 0.449640 59.0 0.2795
IH SNC 1 176 0.134722 77.0 0.3530 177 O.l62327 70.0 0.3530 178 0.032171 84.0 0.2350 179 0.239762 72.0 0.4410 180 0.129143 66.0 0.2350
4-43
TABLE 4.3-1 COMPILATION OF CHASE CAR MEASURENENTS ( contd.)
VEHICLE CONDITION RUN NO. GEOM LASER VISIBILITY
IH SNC 2 181 0.465270 72.5 0.5290 182 0.352223 86c0 Oe5590 183 0.244499 72.5 OG6180 184 0.335125 70.5 0.5880 185 0.513654 88.0 0.6180
IH SNC 5 201 0.185798 80.0 0.5590 202 0.267791 69.0 0.5590 203 0.199329 79.5 0.5880 204 0.182647 164.5 0.6180 205 0.289541 79.5 0.5590
IH SNC 2 230 0.278435 84.5 0.8820 231 0.318170 73.5 0.7500 232 0 .. 181 041 83.5 0.7205 233 0.305410 95.5 0.7205 234 0.362300 91.0 0 .. 7645 235 0.386950 94.5 0.8825
IH SNC 5 247 0.238533 69.5 0.4115 248 0.324148 73.0 0.3680 249 0.180264 77.5 0.3530 250 0.254203 90.5 0.3820 251 0.319337 76.0 0.4265
IH SNC 1 258 0.196433 65.S 0.3090 259 0.131400 77 .. 0 0.3385 260 o. 151212 47.0 0 .. 2500 261 0.196571 62 .. 5 0.2650 262 0.154114 50.0 0.3090
IH LNC 1 311 0.847467 80.9 0.5735] 312 0.490302 74.5 0.5295 313 0.789791 68.0 0.5440 *Not Used 314 0.918804 66.5 0.4855 315 0.738669 7.2.5 0.6030
IH LNC 2 316 0.823592 73.0 0.6030] 317 0.669985 84.0 0.-5885 318 0.683704 76 .. 5 0.'6615 *Not Used 319 0.424476 73.5 0.3380 320 OG462448 68.5 0.4560
IH LNC 5 338 0.909312 '60.0 0.5885] 339 0.934666 59.5 0.6030 340 0.822514 84.0 0.4560 *Not Used 341 0. 7-61062 67.0 0.4265 342 0.877.214 76.0 0 .·6030
4-44
TABLE 4.3-1 COMPILATION OF CHASE CAR MEASUREMeNTS ( contd.)
VEHICLE CONDITION RUN NO. GEOM LASER VISIBILITY
IH LNC 5 348 0.443538 73.0 0.4705 349 0 .. 144593 57.5 0.3970 350 0.637181 79.5 0.6030 351 0.554720 82.0 0.4410 352 0.706270 70.0 0.5295
IH LNC 1 358 0.169956 6S 0 0.3530 359 0.202931 60.0 0.1325 360 0.240487 72.0 0.3240 361 0.110417 60.5 0.2650 362 0.092952 58.0 0.2945
IH LNC 2 363 0.247186 83.5 0.6030 364 0.390156 72.0 o. 5145 365 0.243610 70.5 0.4560 366 0.396753 89.5 0.5590 367 0.211915 81.5 0.5000
*Wind out of SW, blew spray away from Sensors 5 & 6.
4-45
wind was out of the southwest on those runs, and hence readings of
lasers 5 and 6 were not primary data$ These runs are noted in Table
4.3-1.
A number of Pearson product-moment correlation coefficients were
calculated. This statistic may be defined as
r =~ 2_(~ ·...1..) N sx sy
where N = number of paired observations to be analyzed in the 2 sets of data.
£.. = directs summation x = an observation y = x's equivalent paired observation 5x = estimate of the standard deviation of the set of x's sy = estimate of the standard deviation of the set of y•s
The correlation coefficient expr.es·ses how well knowing one
measurement can permit a prediction to be made of the other measurement.
An "r" of 1 represents a perfect relationship; an r of z.ero or close to
zero expresses no correlation or relationship. Negative values of r
express an inverse relationship. Several different correlation
coefficients were calculated:
(a) for each vehicle and condition
(b) for each vehicle lumping together conditions
(c) all data taken as a whole.
4-46
For each of these comparisons, two coefficients were calculated,
one between the geometric mean of lasers 5 and 6 and the chase car laser
reading; the other between the geometric mean of lasers 5 and 6 and
target visibility.
In addition, an ~stimate of level of significance of each
correlation coefficient was made, under a "no correlation" hypothesis
set at a rejection level of 0.05. A value of r had to be high enough to
make the probability equal or less than 0.05 that such an r could occur
with no real relationship existing to be declared a "significant"
difference.
Table 4.3-2 gives the results of this analysis. In this Table, the
vehicle is identified in the first column, the condition or treatment in
the second column, then the means of each variable over the number of
cases used in calculating the correlation. The last two columns give the
value of r for first the relationship between the stationary laser
reading and the chase car laser reading, and seco~d the stationary laser
vs. the visibility observation. If vehicle and conditions are considered
separately, no correlations are significant for the COE, although for
Condition 5 both approach significance, and all are in the right
direction. For the SNC, most of the correlations are inverse although
non-significant. This means that the higher tne stationary laser
reading, the lower the chase-car laser reading, and the lower the
visibility ratio.
The best estimate of relationship is probably the se~ond analysis
which pa-rtials out vehicles but pools data a.cross .conditions for the
same vehicle.
4-47
TABLE 4. 3-,2
M E A N S "r" of Geom. vs. : VEHICLE CONDITION GEOM LASER VISIBILITY LASER or VISIBILITY
COE 1 24 .. 4 66.7 0.27 0.070 0.357 2 40.9 73.8 0.40 0.258 0.435 5 53.2 80.9 0.44 0.57 3 0.550
LNC 1 46.0 68.1 0 .. 41 0.597 0 .. 842* 2 29.7 79.4 0.53 0.145 0.217 5 49.7 72.4 0.48 0.739** 0.780**
SNC 1 15.3 67.1 0. 31 -0.380 0."594 2 34.0 82.9 0.69 0.112 -0.307 5 24.4 85.9 0.48 -0.421 -0.347
Across Conditions
COE 39.5 73.8 0.37 0.609* 0.671* LNC 32.0 71.9 0.43 0.507 0.606* SNC 24.9 78.8 0.50 0.127 0.584* ALL DATA 32.3 75.4 0.43 0.210 0.301*
*Significant at 0.05 level **N=5, too sma 11 for meaningful test of sig.
4-48
If the relationship between the in-car laser measurements and the
visibility of the target vehicle (using the ratio of time visible over
total time of passage as an indicant) is evaluated, relatively high
product-moment correlation coefficients result. Table 4.3-~ provides
these findings, all significant at the 0.05 level. These correlations
reflect the degree of correspondence between what the laser is measuring
through a windshield and through which human observers are also
glimpsing a target vehicle.
In su11111ary, it appears that a modest but definite association
exists between stationary laser readings and extent to which human
observers can discern a target through the spray cloud. An even stronger
relationship exists between the laser measurements made in the car and
visibility. But the relationship between stationary laser readings and
moving car laser readings is rather low to nonexistent.
For the LNC, correlations are higher and positive, especially
between stationary laser readings and visibility. Because a number of
runs were eliminated for conditions 2 and 5, these correlations should
not be taken as representative, although they are certainly impressively
high at first glance for Condition 5.
Considering the fact that different cab configurations behave very
differently with respect to amount of spray production, observations of
spray across conditions might be combined for the same vehicle in ord~r
to improve the estimate of degree of relationship. Indeed, the
calculations of r reported in Table 4.3-2 indicate a significant
relationship between geometric mean of stationary sensors and the in-car
laser as well as between the stationary sensors and visibility of the
4-49
TABL·E 4. 3-3
VEHICLE 11 r 11 of Laser vs. Visibilit~
COE 0.576*
:.NC 0.446*
L"'C 0.758*
ALL 0.·515*
*Significant at 0.05 level
4-50
target vehicle for the COE. For the other two vehicles, significant
relationships exist between stationary lasers and visibility.
When all data are considered together, variability among the three
vehicles degrades the level of correlation, but even so, stationary
laser readings significantly correlate with visibility, although at a
very low value.
4.4 Correlation Between Sensors
The correlation between the sensor readings on the variable
surface and the controlled surface were fairly good. Table 4.4-1
sunmarizes all correlations for sensor 1 through sensor 8.
Sensor 1 and Sensor 2 readings did not correlate with Sensor 5 and
Sensor 6, respectively, as well as sensor 3 and sensor 4 readings did
with sensor 7 and sensor 8, respectively. The four correlations were
.620, .499, .842, and .850, respectively.
The correlation of sensor 7 readings and sensor 8 readings was
.847. Thus sensors 1 and 2 correlated as well with their matched sensors
as sensor 7 did with sensor 8. The interested reader may find more
detail on this study finding in Volume 2.
4.5 Results of Special Studies
Two very small-scale studies were performed in the course of thi·s
project. One was run during the tests in Study A with the LNC tractor.
This study was comprised of five runs (one was unusable) in which the
tractor was equipped with its original equipment manufacturer (OEM)
aeroaid, but was otherwise untreated. These runs were then compared with
the baseline treatment runs on that same day and thus under similar wind
4-51
Table 4.4-1
CorTel ations ·Bet\Een Sensors 1 Through Sensa- 8
Selsor 1 Selsor 2 Sensor 3 Sensor 4 Se1sor 5 Sa'lsor 6 Sensor 7 Sertsor 8
Sensor 1 1 .754 -.491 -5.10 .620 .595 -.320 -.?ZI
Se'lscr 2 .754 1 -.281. -.275 .387 .479 -.100 -.193
Sensor 3 -.491 -.281 1 .813 -.481 -.450 .2A2 .7Frl
Sensa- 4 -.510 -.275 .873 1 -.514 -.463 .768 .89)
Sensor 5 .620 .Jf!l -.481 -.514 1 .f!J7 -.4BS -.a:o Sensa- 6 .595 .479 -.400 -.463 .f!37 1 -.491 - .. ·549
Sensor 7 -.320 -.1al .842· .768 -.48f3 -.491 1 .eA-7
Sensor 8 -.?J!l -.196 .787 .8&) -.6CX) -.549 .847 1
4-52
conditions, using Rule 4 as usual. Since only two conditions were
compared, a simple t-test of the diff.erence of independent means
sufficed. The results of this test are given in Table 4.5-1. The results
show a highly significant difference (probability 0.0194) in means. This
suggests that the baseline mean of 2.73 (natural log of the Rule 4
geometric mean = 15.58 percent as calculated by raising to the mean +
1/2 the variance) is much less effective than the aeroaid in controlling
spray, since the aeroaid condition mean percentage transmission works
out to 50.09 percent. Put another way, the aeroaid alone does almost as
much as a complete treatment with aeroaid, which suggests that the major
contributor to spray suppression on this particular-vehicle is the
aeroaid. The reader is cautioned not to infer too much from a
small-sample preliminary study such as this.
The second mini-study was a comparison between a full treatment
(treatment 5) and that same treatment with the addition of side-fairings
to complement the aeroaid. This study was done by running five extra SNC
runs with side-fairing during Study A, and comparing the data thus
obtained with the companion five runs done that day with the vehicle
equipped with Treatment 5 only. The results are shown in Table 4.5-2.
There was no significant difference between these two treatments; the
side fairings had no effect. This finding should be considered in the
light of the finding in Study A that the aeroaid on this particular
tractor actually hurt spray suppression rather than helped. The small
sample size prevents these results from being conclusive in any case,
but they are perhaps worthy of consideration.
4-53
TABLE 4.5-1
VARIABLE: lNRUlE4
CONO
1(BASELJNE) fA
N
5 4
MEAN
2.73089843 3.87210843
FOR HO: VARIANCES ARE EQUAl, f'=
RUN AREA
353 1 354 t
.J:::o 355 2 I 356 2
<.fa 357 9 .J:::o 358 2 359 2 360 t 361 t 362 1
STO DEV
0.40312050 0.57857640
PHASE II TRUCK SPLASH STUDY BASEllNE+AERO VS. BASELINE
TTEST PROCEDURE
STD ERROR
o. 18028097 0.28928820
MINIMUM
2.22949384 3.01459688
MAXIMUM
3. 18008097 4.24986072
2.06 WITH 3 AND 4 OF PROB > f'• 0.4965
PHASE II TRUCK SPLASH STUDY LIST Of DATE FOR MODElA
CONO PERC5 PERC6 PERC7 PERC&
tA 48.3 8.6 87.2 99.4 tA 85.4 50.7 67.5 84.9 fA 74.7 43.0 59.1 93.6 u 86.2 57.0 58.3 83.5 1A 89.9 51.8 73.1 90.3 1(BASELINE) 26.5 10.9 48.3 89.9 1(BASELINE) 37. 1 t 1. 1 20.4 72.4 t(BASELINE) 35.7 16.2 2t.O 54.2 1(BASELINE) 12.7 9.6 76.9 97.0 1 (BASELINE) 24.0 3.6 47.5 95. 1
VARIANCES T
Y4
UNEQUAL EQUAL
20.3809 65.'801t 56.6754 70.0956
16.9956 20.2931 24.0487 11.0417 9.2952
-3.3480 -3.4995
LNRULE4
3.01460 4. 18664 4.03734 4.24986
2.83295 3.01028 3. 18008 2.40168 2.22949
Of PROB > ITI
5.2 7.0
0.0194 0.0100
TABLE 4.5-2
VARIABLE: LNRULE4
COND
5(FULL) SA
N
s s
MEAN
3.24831637 3.17802579
FOR HO: VARIANCES ARE EQUAL, F 1 =
RUN
247 248
.J:::o 249 I 250 oi
<.n 251 252 253 2S4 255 2S6
PHASE II TRUCK SPLASH STUDY CONDITION 5 + SlOE FAIRINGS VS. COND.ITION 5
TTEST PROCEDURE
STD DEV STO ERROR MINIMUM MAXIMUM
0.24108539 0.06990814
0.10781667 0.03126387
11.89 WITH 4 AND 4 OF
2.89183566 3.10530004
3.47861546 3.28365257
PROB > F 1• 0.0342
PHASE II TRUCK SPLASH STUDY LIST OF DATA FOR MODEL 8
AREA COND PERC5 PERC6 PERC7 PERC8
1 5(FULL) 32.7 17.4 90.4 94.5 2 5(FULL) 59.7 17.6 89.3 94.2 6 5(FULL) 33.5 9.7 92.4 97.6 1 5(FULL) 36.1 17.9 82.0 90.8 6 5(FULL) 60.7 16.8 73.7 88.7 6 5A 33.2 15.0 89. 1 95.6 1 5A 46.5 15.3 78.8 89.1 6 5A 41. 1 14.5 90.9 97.8 1 5A 52.2 11. 1 81.3 93.1 6 SA 33.0 15.7 83.4 96.6
VARIANCES T OF PROB > ITI UNEQUAL 0.6262 4.7 0.5608 EQUAL 0.6262 8.0 O.S487
Y4 LNRULE4
23.8533 3.17192 32.4148 3.47862 18.0264 2.89184 25.4203 3.23555 31.9337 3.46366 22.31S9 3.10530 26.6730 3.28365 24.4121 3. 19508 24.0711 3.18101 22.7618 3. 12508
4.6 Initial Splash Phenomenon
Figure 4.6-1 illustrates this phenomenon, which as been informally
noted but not evaluated on both phases of this MVMA sponsored program.
These photographs were made from videotapes. The initial splash of water
appears to come from the leading edges of the st.e.ering axle tires vary
1_ ike that observed with watt.or skis. The jets of water are di rect.ed under
the vehicle where they are tlown backward at an angle of 30 to 45
degrees upward and diagonally outward such as to miss entir-ely any
.. conventional" treatment of skirts and flaps. This jet of water on each
side moves out into the slip stream produced by the motion of the test
vehicle where it literally explodes into spray. None of the treatments
so far evaluated in Phase 1 or 2 control this source of spray production
in any significant way.
4-'56
Figure 4.6-1 Initial Splash Phenomenon (from Videotape)
4-57
5.0 SUMMARY OF FINDINGS AND RECOMMENDATIONS
5.1 Summary of Findings
5.1.1 Answers to Fundamental Questions
The fundamental questions identified in Section 1.2, Objectives,
will ue repeated in different order in this section and answered on the
basis of the results of this project.
GENERAL STATISTICAL QUESTIONS
Is it appropriate to "average" over wind conditions, as reco11111ended in
the technical report (Phase 1), or does this "averaging" tend to dilute
treatment effects?
Using the mean (either geometric or arithmetic) of all sensor
rea6ings on a run, with no reference to where the wind is blowing the
spray does tend to produce an overly conservative or "diluted"
comparison of different treatments, which may be misleading. There are
simple methods for improving and removing bias from the data for the
purpose of comparing treatments. These methods are referred to in this
report as 11Rule 4" which will be summarized below.
If "averaging" of sensors is appropriate, is the arithmetic mean the
best measure of this "average .. or is the ·"geometric .. mean more
appropriate?
Unless single sensor data is used (a simplifi·cation of Rule 4)
some kind of summary statistic is necessary in order to make comparisons
among treatments. "Averaging" or the arithmetic mean is the most
5-1
commonly accepted way of accomplishing a summary number. The geometric
mean, a lesser known summary statistic, is useful when the distribution
of the data points is known to be other than normally (bell-shaped
curve) distributed. Spray density diminishes as a complex function of
the distance of the sensor from the source of spray; it is not normally
distributed. The geometric mean tends to produce 1n art i fi cia 1
"normalization .. of the data, which, as long as it ;s consistently
applied, should have no biasing effect on the data which are used for
analysis, but rather render that data more suitable for the kinds of
statistical tests (parametric ones) used. Analysis of the data using
both arithmetic and geometric means, in any case, has had no appreciable
.effect on the conclusions reached.
How are the conclusions on the effectiveness of splash and spray
suppression devices affected by wind?
By using the double strategy of selection of runs from the ample
(16) runs made for any given treatment for similar wind conditions, and
by using wind area as a co-variate where selection resulted in too few
runs for valid statistical comparisons to be made, and using of Rul,e 4,
comparisons of treatments for spray suppression are not affected by wind
conditions. Wind conditions did not vary systematically enough for sound
comparisons of the same treatment under di ffer.ent wind conditions to be
made. The rule adopted for treatment of the dependent variable thus
r.endered the dependent vari ab 1 e invariant with respect to wind.
What is the best statistical method for incorporating the effects of
wind into the treatment evaluation process?
The best method that we have found is the method id.entifi.ed as 11 Rule 4", which consists of mapping wind direction and velocity onto a
5--2
polar plot, and then using only those ·sensors which are affected most by
the cloud of spray as it is blown to the quarter which the polar plot
identifies. This method of handling wind assumes that the quantity of
water thrown into the air by the tire-pavement interaction is a
constant, and that wind conditions affect where that water thrown into
the air can be found, but not how much. As a further refinement to
correct for different variances, the natural logarithm of the geometric
mean of the sensors selected by Rule 4 is actually used in the analyses.
It is noteworthy that a much more elementary treatment of data for
windage, that of merely taking the lowest percent transmittance of the
four sensors on any given run, gives very similar results and leads to
similar conclusions. The method of handling the data for wind also calls
for using data with similar wind conditions as much as possible, and
co-varying wind with treatments otherwise. This treatment of the data
appears to be very straightforward, takes wind into account ir. two ways,
and provides consistent results. The Rule 4 method results in a measure
of spray reduction which is independent of the wind effects at the time
of the run.
STUDY A QUESTIONS
Is visibility significantly improved by adding aeroaids and spray
suppression devir.es in varying configurations?
In general, yes, but with very important qualifications. Treated
vehicles always produced less spray than untreated (baseline) vehicles,
but these differences were sometimes trivial and not statistically
significant. This is a finding consistent with Phase 1 results. How much
improvement w~s obtai ned for a given tr~eatment was vehicle-dependent.
5-3
A 11 tr.eatments for a 11 vehi c 1 es i nvo 1 ved flaps on a 11 whe.e 1 s, except
baseline which had plain flaps on the rear axle only. On COE tractor-van
trailer combinations, treatments with aeroaids performed somewhat better
than treatments without aeroaids, but all treatments that involved
skirts on at least the drive and rear ~xles performed significantly
better than the minimal treatment of installing skir+s on the rear axles
only. This treatment, the NHTSA 1-year Rule proposal, was no better than
baseline.
On the SNC tractor-van trailer combination, the aeroaid appeared
to degrade spray suppression -compared to the best treatment, which was
the NHTSA 4-year proposed treatment, skirts on all axles, no aeroaid.
Deleting the steering axle skirts on this vehicle (as on the SOE) did
not make a statistically significant difference, but any other treatment
was significantly less effective in controllin·g spray. Baseline was
least effective, significantly less so than the NHTSA 1-year treatment.
The LNC tractor-van trailer combinations behaved similarly to the
COE, but with less clear-cut results. The two treatments with aeroaid,
which differed only in whether or not steering axle skirts were present,
performed equally well, and better than anything el s.e. Other treatments
perform about the same among themselves. All treatments were
significantly better than baseline.
Thus in Study A it appears that the NHTSA 4-yecr tr-eatment
provides reliably better spray control than the 1-year, which tends to
be little better than baseline. An aeroaid can further help spray
suppression on certain vehicles, but can actually hurt on oth,·rs, and
thus cannot be considered to be a uni versa 1 panac.ea for spray control •
5-4
In the course of running this study, a source of spray production
was noted that is not affected by any of the treatments so far evaluated
in any of these series of tests. This phenomenon will be described below
under "Other Findings."
5.1.2 Study B Findings
Water depth on the pavement appears to have a reasonably linear
relationship to spray production and its control, such that a given
treatment will provide the same amount of reduction over what would be
produced if no treatment were applied. There may be a point of
diminishing returns as water depth increases, however. At depths where
this might occur, the vehicle is near hydroplane depth (0.25 inch of
water or deeper).
5.1.3 Study C Findings
The final fundamental question asked by MVMA was,
Are splash and spray suppression devices statistically more effective
for van semi-trailers than for tankers and flatbeds?
Yes. The NHTSA 4-year proposed treatment of skirts and flaps on
all axles produced no improvement over· baseline on an LNC tractor-tank
combination. The amount of spray produced by the vehicle in baseline
configuration with a tanker trailer was comparable to that produced by
that tractor with a van trailer with the NHTSA 4-year treatment. An
unloaded flatbed trailer does not profit from the application of the
NHTSA 4-year treatment as far as spray suppression is conc.erned. Without
treatment, such a vehicle produced spray at a level comparable to that
produced by the best of the tractor-van trailers with treatment (LNC),
5-5
and far better (less spray) than the same tractor (SNC) with a van
trailer with the best treatment. When a turbulence-producing load was
placed on the flatbed, spray production doubled, but improvements in
spray control with the NHTSA 4-year treatment were only marginally
better than baseline. Thus treatments do not produce nearly as much of a
difference in spray production on trailers other than vans, if these two
trailers are at all representative.
5.1.4 Chase Car Findings
A definite though modest relationship exists between stationary
laser r,eadings of a spray cloud and the exte~t to which human observers
can discern a target through that cloud. Human observers• reports of
visibility can predict (somewhat) laser readings. A stronger
relationship exists between laser instrumentation in a chase car and
those same indicants of visibility through a spray cloud, but a
paradoxical and low to non- existent relationship can be identified
between stationary laser and moving chase car laser readings. Chase c~r
instrumentation shows some promise, but it cannot be assert.ed that the
correct methode 1 ogy or approach to data r-eduction has yet been
discovered. Thus the hoped-for br-eakthrough to permit spray attenuation
devices to be evaluated under highway rather than closed-course
simulated conditions of wet weather has not occurr.ed. There i·s, however,
sufficient encouragement in these findings to pursue the chase car
instrumentation and observation approach further.
5-6
5.1.5 Other Study Findings
A very circumspect evaluation of the effects of an aeroaid without
any other treatment for spray control suggests that with at least
one kind of tractor (LNC) the effects can be major. For a vehicle on
which an aeroaid has a rather negative effect on spray attenuation,
installing of additional devices to smooth air flow and lower air
resistance--side fairings--results in no significant difference. The
results of these two mini-studies point out the very complex interaction
effects of aeroaid, flap/skirt treatment, and cab configuration on spray
generation.
Finally, a phenomenon noted on a casual basis during both studies
should be identified as a potential major source of spray which is
evidently not treated by any of the devices so far developed or
evaluated by anyone: the initial splash from the forward edge of the
steering axle tires. The outward-directed jet of water so produced moves
upward into the slip stream and is transformed into spray which may
play a significant part in the cloud produced by heavy vehicles moving
over wet pavements on the Nation's h·;ghways.
5.2 Recommendations
1. Further research and development should be undertaken by industry
to gain a better understanding of the initial splash phenomenon and
to develop treatments to deal with it.
5-7
2. All future evaluations of any splash and spray control treatments
using the stationary laser measurement approach should use the
"Rule 411 reduction and selection of data to assure comparability
of findings.
3. The instrumented chase car approach to measuring spray from heavy
vehicles should be further explored to find a way to move spray
control device evaluation off the test track and into the real
world.
4. Industry and regulatory agencies at both the state and national
level should be cautioned not to expect too much from the
installation of skirts and flaps on all wheels. Partial treat
ments may be very disappointing indeed in not producing
perceptible changes so far as the motoring public can see
in the amount of spray generated as compared to no tr.eatment.
It may be ne,cessary to devise a performance rather than a process
or prescriptive standard for spray suppression, since thes.e
treatments are so vehicle-specific and may not work at all on
trailers other than vans. What kind of testing or certification
might be suitable can only be conjectured, and would require much
additional work.
5. Manufacturers of truck tractors ~onsider aerodynamic gains as a
major design goal. Trailer manufacturers may well feel likewise.
These designs should include consideration of spray ·control, and
should be tested for their spray ·control capability. In the future,
5-8
add-on devices for spray attenuati.on should yield to integration of
this important function into the overall design of the commercial
vehicles that will be on the Nation's highways in the 1990's and
beyond.
5-9
REFERENCES
1. Kappa, R.J., Zimmer, R.A., Ivey, D.L. and P-endleton, 0 ... Heavy Truck Sp 1 ash and Spray Testing,.. TTI Fi na 1 Report, Project RF7002, Agreement TTI 8413-C9191 with Motor Vehicle Manufacturers Association, Detroit, Michigan, September 1984.
Vol. 1: Summary and Findings Vol. 1A: Statistical Analysis Stipplement Vol. 2: Test Log and Photographic Record
2. Weir, D.H., Strange, J.F., and Heffley, R.K. "Reduction of Adverse Aerodynamic Effects o"f Large Trucks ... Final Report, Contract No. DOT-FH-11-9165, Systems Technology, Hawthorne, CA., September 1978.
3. Johnson, W.A., Stein, A.C. and Hogue, J.R. 1'Full S<:ale Testing of Devices to Reduce Splash and Spray from Heavy Trucks ... Systems Technology, Inc. Contract DTNH22-80-C-07078 with National Highway Traffic Safety Administration, u.s. Department of Transportation, January 1985.
4. Department of Transportation, National Highway Traffic Safety Administration, 49CFR584, ••splash and Spray Suppression Devices, .. Notice of Proposed Rulemaking, April 8, 1985.
5-10
APPENDIX A
COMPILATION OF ALL RUNS
KEY TO COLUMN ENTRIES
RUN = Run number assigned by Test Conductor
AREA = Wind area, see Figure 4.1-1 in text
WINDDIR = Wind direction, 0-360° velocity of 0 assigned wind direction of 000 (North)
WINDSPD = Wind speed, MPH
PERCN = Percent transmission (minimum) for sensor n
PG£05678 =Geometric mean of sensors 5, 6, 7, 8
ARITH 5-8= Arithmetic mean of sensors 5, 6, 7, 8
Y4 = Rule 4 reduction of data (see Section 4.1, text)
LN RULE 4 = Natural logarithm of rule 4 data
SETUP =Treatment (see Figure 3.1-1)
A-1
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... .,., 2 110 4 20.3 :1.~'2 21.<1 12.:1 2t.l 12.ll 22.1 Ia. I 21.&:104 :SO.I'fS 21.1:104 2.21116 ::1"71 2 110 I 12. I 0.20 20 .• 2"7.2 ..... , 11.2 2"7.1 12.1 :12.'73<11 :11.4'71 :12. '7:S•I 2.4•••• 3"71 I 1'70 t 1.:1 0.01 2o.a '10.1 3'7. I 2:1.1 24. I '1'1. 1 :aa.12'Pt ao. 121 21.7'J'72 :1.:113'71 210 2 110 T tl.l :z.so 21.0 21.1 2'7.'7 11.4 21.1 a:z.t :U.21fl &2 221 21.::1:1'71 :1.2'7101 211 I 160 I 1.1 0.;)0 2&.'1 1'1.1 20. I lt.l 2"7.4 11.2 20. 1000 ::11.221 II. 4211 2 't 31'7 212 1 121 '7 3.'1 O.Ot '7<1.0 11.1 2'7.1 20.2 2<l.l 11 .I :11.11'71 4:1.5'75 %:1. 11'72 ::1.11121 :u::r ' tiC 10 22.' I. tO 22.1 32.1 10.1 ::11.1 t.l :13.2 :10.1'7'70 21.710 ::10. &'J'TO 3.4::1001
·········•···•·•·•···••·····•·•·•·••••·•••·••••·• TltUCX•IH ~•c SITU It 01' TltUCX•IA ·•·••·•····•····································· !lUll ..... WtNOOill WINOSitO lttACI JteltC2 ll'lltC3 ~tiiC4 ll'tJtCI ltiMCI .... c., JttJtca ltC101.'71 AIUTMI_a .,. I.HilU~&4
21:1 I 100 " 21.:1 I. 3 ..... . ., .. <II. :I 1.1 1'7.2 11.1 <l3.1111 10 .• .,. 20.:1101 3.01610 :ssa I 1:11 2 &2.0 10.2 33.1 '71.0 ••. 4 10.'7 1'7. I •••• 70.1'710 '72. 121 11. ao1; 4 11116 21!5 2 110 I 2'7.2 4.4 '7:1.0 l't,O '74.'7 <1:1.0 II • I 1:1.1 ..... 212 1'7.100 11.1'71<1 4 0:1'126 :lSI 2 110 2 21.0 1.1 '7:1.1 II. 0 &1.2 • .,.0 sa.:a 1:1.1 11.1:12:1 , %10 TO.OIII • 2<11&1 :IS'7 I 0 0 41.2 II. I 42.'7 '71.1 •••• 11. I '7:1. 1 10.2 '74.4101 'JI. 2'7S
A-6
,.MAS I' II TltUCIC SJIII.ASH STUDY LISTING 01' DATA JI'Oit STUDY I
···············································~·-··· SITU,. 01' TltUCKri(IASILIN!I ·········································-·········· It UN WATDIJIITM Alti'A WI NOD lit WINOSJIIO ,.lltCS l"t!ltCI l"lltC7 l'lltCI I"CI0$1'71 AIUTHS_I y" LNitULII
102 SHALLOW 7 110 12 11.'7 1:7 2. I IS .I 11.2017 II. tOO II. 2017 2.11112 10:1 SHALLOW • 170 f:l 11.7 1'7.1 10.7 IS.I 22.1111 :13.0'75 31.3111 2.17373 104 SHALLOW '7 110 fl 71.1 u.s 1.1 23.1 21. '7101 20.1"1'5 21.7101 3.01011 lOS SHALLOW 7 110 II 11.4 11.1 IS .I 41.1 21.321'7 32.200 21.3257 3.3 .. 377 101 SHALLOW '7 110 IS 11.1 11.7 2.1 II. I 15.22:10 21.710 15.2230 2.72211 10'7 SHALLOW '7 110 " 41.1 21.:1 41. I 11.1 41. 11'71 1:1.200 II. 11'1'1 3.1'1' .. 11 101 SHALLOW '7 110 14 11.1 :1'7.1 11. I 10.2 31.10'11 12. ISO 31.10'14 3.111'7• 101 SHALLOW ., 110 II 11.'7 14.'7 40.'7 12.'7 1'7.0130 '71.110 1'7.01:10 4.20113 110 SHALLOW '7 110 t2 11.1 41 •• 32.1 31.0 41.41'71 50.421 41.41'71 3.13140 111 SHALLOW I flO tl 10.1 11.1 11.2 11.2 12. 2'7:11 13.110 13. 1124 2.1'7::131 112 SHALLOW I flO II 11.1 1'7.1 40. I II. 1 u.31ol '74.0'71 11.11&3 3. Ill SO 113 SHALLOW 7 110 12 11.1 11.'7 10.2 12.1 '71 .200'7 '75.010 '71. 200'7 4.21110 114 SHALLOW '7 110 " 10.1 II. I 21.1 22. I 1'7. 2'711 11.110 4'7. 2'711 3.11100 111 SHALLOW I 110 13 II. 1 11.1 II. I 2'7.1 40.2211 10.000 21 .2401 2.01011 Ill SHALLOW ., 110 11 n.1 31.:1 '7.3 2'7.0 2'7.1101 34.1'71 2'7. 1101 2.2111:1 liT sHALL. OW '7 110 11 II.S 12.1 1.2 24.1 :11.1245 12.'750 31.1241 3.1'7203
1 MIDIUM I 0 0 23.1 4.1 1.1 11.1 1.1'7'71 12. SIO 2 MIOIUM • 0 2 1:1.1 1.1 s.o 14. I 13.1310 22.1'11 :1 MIDIUM I 221 :s :1'7.'7 4.4 1.1 "'. 2 1.1341 11.310 2.1122 1.3'7421 4 MIOIUM I :140 I 71.1 14.2 1.2 1'7. 4 20.0123 21.100 I MIIDIUM I :sao I 11.3 1.1 :1.'7 13 .• 1.1712 10.1'71
11 MIIOIUM 2 110 ., 21.1 20.1 20.1 12.1 :12.1312 40.121 24.1'713 :a. 11'711 12 MID tUM 2 140 ., 2:1.1 13.1 21.'7 11.1 30.5'7:11 40.'710 11.2211 2.$0211 13 MI!DtUM 2 110 '7 21.1 fl. I 11.2 15.2 20.1111 31.1'71 22.111'7 3. 13313 14 MI!DlUM I 110 I 31.2 20.1 :as.• 12.1 :II. 1311 41.210 2'7.4401 3.31201 IS MI!DIUM • 110 I 23.3 II. I tS.2 11.1 45.02:1'7 St. 1'75 20.11'1'1 3.03511 II MIDIUM I 110 11 30.3 3<&. I 11.3 11.0 S I. SilO 51. 1'75 32.1431 3.4'7022 IT MIDJUM '7 110 I 3'1'.. 1.1 4.1 2:1.0 13.5111 11.4'71 13.5151 2.1015 .. Ia MIDI liM I 110 10 11.1 13.'7 1.7 "·I II. '7101 21.221 11.1&11 2.&1130 II MIDIUM '7 110 10 21.3 1:1. I 4. I 3S.3 ,. .7112 11.410 11.1112 2.1145'7
100 MI!DIUM '7 110 10 21.2 S.l " . ., II. I 1'7.2111 24. ISO 17.2111 2.14511 101 MIDIUM '7 110 10 13.2 24.:1 1.1 12.0 ". 3110 31.325 II. 3110 2.11312 131 01111" ., 110 12 7T.I • 1 •• 12.3 20.1 21.'711'1 IO.SIO 31.711'7 3.451.&3 13'7 011111' ., 110 14 2<&. I 1.0 4.2 21. I 12.05'7:1 15.100 12.0$'73 2.11111 131 Dill II' ., 110 11 '71.1 41.1 13. I 20.1 30.'7SII 31.125 30.1511 3.42&01 t:st OIIJII '7 110 1:1 10.3 II. I 1S.S :11.1 31. 1'721 11.410 31.1721 3.11215 110 OIIJII ., 110 1:1 14.1 II. I 4.1 1.1 u.saoo 21.510 IS. ISOO 2.'7140& Ill Dllll' ., uo 14 <&2. 1 s.:s 4.1 20. I 12. 11'71 11.200 12. 11'71 2.50012 142 0111" '7 110 14 11.1 '71 .0 4.0 21.1 21.4255 1'7 .100 21.1251 2.3 .. 121 113 01!1!1" '7 110 u '71. I 14.'7 5.'7 20.3 11. '7001 21. 1 so 1&.1005 2.12155 112 DI!I!JII I 200 ,. 12.0 1'1 • I ••• 11.1 2'7.2'111 42.'1'00 10. 1054 2.31301 113 DIIJII ., 110 14 .,. • I Sl.l 13 .• 24.0 :11.011'7 13.SSO 31.011'1 :J.ISIIO til 01!1" ., 110 11 10.'7 21.0 I I •• 1'7.1 21. 1'7'32 34.121 21. 1'732 2.21&74 ISS DIII!JII '7 110 " 11.'1 31.3 '7.2 12.1 22.2111 :14.210 22. 2tlt 3.10450 til Dll" '7 110 14 2<L4 4.1 2.1 31.1 10.'7302 1'7.121 10.'7::102 2.3'130'7 11'7 OII!JII I ItO 13 14.1 1.4 1.0 13.0 14.7'71 .. 21.000 10. 1110 2.:12220 Ill DI!IP '7 110 14 '71.2 43.5 1.1 2::1.0 21.4SSS 31.100 21.4111 3.31211 lSI 01!1!11' I 200 IS 10.1 51.3 1.'7 20.'7 30.1'711 I 1. '7'71 1&. 1'700 2 .IS 113
"HAS I II TRUCK SI"I.ASH STUDY LISTING 01' DATA I'Oit STUDY •
·····-··············-··-·············-··············-- SITUt' a,. TltUCK•I(I'ULL) ·····················-··················----·········· It UN WATDIJIITH &It lA WI MOD lit WIMOS,.O I"IJtCS Jli!JtCI Jlll!ltC'7 Jlll!ltCI ,.Gt!OSI11 AltiTMS_I Y4 LNitULE•
I IS SHALLOW I 110 10 '71.7 40.3 11.1 11.1 13.1113 11 ... 25 53.1542 3.11142 1 I. SHALLOW I 1'70 10 12. I '7'7.1 41.1 ••. I 70.3711 '72. 125 1&.21U •-•2:ass 11'7 SHALLOW 7 110 " II. I 11.1 :ZS. I '72.3 II. 211'7 11.4$0 It. 211'1 ... 11521 111 SHALLOW I 110 14 •••• 12. 1 IS. I 14.2 '70. ITS4 '72.000 II. 1133 4. 22 II '7 111 SHALLOW '7 110 12 11.3 11.1 11.1 11.4 10.2111 12.000 10.2411 ... 21514 120 SHALLOW '7 110 10 II. 1 12.1 II. 2 11.1 10.1111 II .300 IO.IS51 4.21310 121 SHALLOW 2 170 ., 13.1 10.4 '71.1 11.1 1'7.154S 11.010 11.11311 4. 52 T 10 122 SHALLOW 1 110 II '71.1 '72.'7 :13.1 72.1 10.'7031 13.100 10.'7031 ... 10519 Ill SHALLOW 1 1.0 II IT.2 13.1 IS. I 4:1. I 41.1211 12.300 15.1211 3.10 .. 51 Ill SHALLOW '7 110 11 14.4 1'7.1 21.2 11.4 10. 444& 1'7 ... '71 10.4441 ... 10113 1'70 SHALLOW I 110 12 ".I '74.:1 10.3 1'7.:1 '73.1TII '71.1121 11.2111 4.1S31& 1'71 SHALLOW '7 110 II 1'7.2 13.3 17.1 40.4 10.0301 12.000 10.0301 3.111212 1'72 SHALLOW I 110 1:1 1'7.4 12.1 11.0 44.1 11.1412 12.4'75 2S.ISIS 3.25124 1'73 SHALLOW 1 110 14 11.1 41.<& 10.1 11.1 ••. 1'711 '10.$'71 II. 1'711 4.22203 1'74 SHALLOW I ItO II 11.'7 11.1 11 .I 20.'7 :II. 14'74 11.1'71 IS. 1141 2.'75331 1'71 SHALLOW '7 110 tl 11.1 IO.S II. 2 14.1 11.1211 14.2'75 11.1211 3.14113
21 MilO tUM I 270 :1 14.'7 '71.5 1.2 11.2 21.4411 11.110 1.1120 2.30111 2'7 MI!DIU.M I 2'70 I 11.1 ••. s 4.1 s.o 22. 11'7 .. ..2.150 1.212S 1. 1:19& I 21 MI!DIUM I 2'70 2 14.0 T'7.1 "' .. 11.1 41.1150 11.000 25.1511 3.2$215 21 MEDIUM s 2'70 2 11. I I I .I 11. I 11.3 44.30'7S 1'1'.'725 22.1'700 3. I 2104 30 MEDIUM I 320 s 17.1 '71.2 1.2 10.1 3'7.4112 $'1.525 41 MI!DIUM • 1'70 10 II. 2 12.1 1'7.1 1:1.'7 11.1001 '70. ISO I&. I 121 4. 221 I I so MEDIUM I 110 12 34.4 1.0 II. '7 11.3 :11.7114 ss.a1o 1'7.5115 2. Ui'll<& s 1 MI!OIUM '7 tao 12 12. 1 14.2 13. 1 12.0 '74.:1'141 75.310 '7<&.3'711 <&.301111 12 MEDIUM '7 110 13 1'7.1 71.0 11. 1 31. 1 44.1211 5&.'1'11 4&.1211 3.102111 13 MI!OIUM I 1'70 10 IS. 1 21.'7 11.1 11.1 11. till 11.410 40 ... S33 2.'70015 14 MI!DIUM • 1'70 12 40 .'7 12.1 12.4 1'7.4 11.1231 ao.4SO 22.S13S 3. 13 I 13 72 MIOIUM I 1'70 I 12.0 2'7.'7 14.0 11. '7 $4.0011 14.aSo 41.4111 3.72&24 '13 MI!DlUM 1 110 10 1'7. I '71.1 10.1 10.1 42. 11"11 Sl.'700 12.15'71 3.'111.at '14 MI!OIUM ., 140 11 '70.0 31.3 43.7 11.1 53.1114 sa. 100 53.11114 3.11140 '7S MI!OIUM '7 110 I '71.1 31.1 '72.3 1'7.1 11.1143 11.110 14.1143 ".I '7311 '71 MI!DlUM ,. 110 II '71.1 41.2 1'7.2 10. I II. !ISS 1&.100 II. ISS9 4.11201
123 Dill" I 110 12 31.1 12.1 10. I 15.3 11.4$10 st. :ns 22.1111 3. 10005 124 0111~ '7 110 II 13.1 'fO.S 12.5 51.4 ••. 1&11 15.110 45. 1411 3.101111 121 Dill!,. '7 110 IS 12.0 1'7.1 Sl.l 11.2 I:J.a1.:ro as.5so 53.as.:ro 3.11254 121 DC I! I" 7 110 12 51.0 21 ... II.$ 11.1 11.110'7 11.200 51.590'1 ... 01051 127 01:&1" 1 110 11 1&.2 41.4 .. '7.2 II. T 11.3124 14.750 11.3&24 4. IT '1 12 121 0111!1" ,. 110 I I 11.1 II. 1 2.4 21.4 23.2'1.al "'. •2s 23.2'746 3. 14'131 121 01111" I 1'70 10 11.4 11.0 51.'7 15.1 111.3111 '1'0 .100 '10.3'710 ... 2S311 130 DEE I" 1 110 1 1 10.3 14.0 4.0 21.1 2'1'. 1'715 44.525 27. S'I'IS 3.33131 114 DEl! I" I 110 13 1::1.1 '72.1 1.0 24.1 :13.11•4 4'7.300 14. 045$ 2.1451<1 I& I oae:" I 110 12 '71.'1 19.8 2.1 21.4 21.12'15 45.200 I. 1112 2. 11111 1&1 DElli" 4 200 I 4 41.0 11.'1' 3.4 II. 2 22.7111 41 12S 1.9414 I. 11315 I 14'7 OI!I!Jt I 110 II 1:1.0 11.5 5.2 II.& 21.131! 42.425 1.'1'132 2. 1 ...... Ill 0&1!1" 4 ISO 14 40.s 11.3 7. I 21.0 31. 5•U5 15.0'75 13.5411 2.10110 Ill 01:1!1" I :zoo 12 11.2 '70.5 1.5 21. I 30.3110 45.'775 11.1311 2 ... '791 .. 110 0111!1" 4 ItO 11 14.5 81.9 1.1 1'1.1 2'7.&130 4 .. 2'1'5 10. 1 &92 2.32133 IS 1 DEl! I" I 200 14 10.0 1'7. I $.1 211. 1 30.'7112 45.4'1S 12.&711 2.SSSIO
A-7
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'"· 1 lt.:r ..... 21.1 •••• 11.2 12.1'2:1'7 70.021 40. i.Z'71 :I II:ZOT
... 1 !:It I 2:1.1' 2.10 1'7.4 11.2 '74.1 42.1 11.0 11.'7 '72.1241 '71.410 11.414'7:1 4.02144 ••:z ISO .. 42.'f t2.'70 12 ... 41.0 '72.7 :11.4 '71.3 11.1 1'7.11U '70.400 12.111'7 :t. IIIAI 442 tSO • II. I :Zt .oo 2:1.0 12.1 '74.4 22.1 Tl.l .... ••. 1:111 11.210 41. 1141 :s. 1 11t1 441 140 I 2?.:1 :1.20 It. I 1:1. t 10.1 41.'1 14.1 11.2 '12.1221 '71. 110 T:t.I:Z21 4.:10111 441 110 I 1.,.1 12.10 20. I 11.1 11.1 11.0 12. I •••• 11.21tt 11.&71 :11 . .0457 2.11100
·············•·•···•••···•·•·••·•••••••··••••· TIIIUCX•T SITU II' ... TltUCX•2(NitTS&C4YIIIIJ ··••••··••····•····················•·········· ltUII ARIA ..,, .... , .. ......... l"lllC1 111CilC2 I"IRC2 .. •• c .. -••c• .. •• c. II'CIIIC'7 I"CIIICI IICaOtl'71 AtUTMI_I Y4 I.NRU\.14
411 .. • 11.2 t.:to '7t.l 14.2 ••• 1 :11.1 11.1 1'7.1 II. 1101 '70. 121 4S.IItl :1.11101
"" 10 2 11.2 I .10 10.4 14.2 13.1 :zt.l II. f tt.' 10. 1'141 14.12S :1'7.1240 :1.1:10:10 411 10 2 t:S. I '.:to 14. I II. I •••• 21.:1 14.1 U.2 10.1121 11.000 :1'1.1411 :1.1:1:1"' 41'7 10 :1 II. t 1.00 1'7.0 12.& lt.l 2t.l tt.2 ... ., II .234'7 11.:12S :11.411:1 2.15021 411 10 .. 2t .I 1.'70 12.1 11.2 11.:1 :t4. I 12.1 tt.4 11.2'1A4 '71. 12S 11.'7201 2.12214 411 10 I 1.1 0.10 1'7.'1 tt.l 11.0 21 '7 1'7.0 100.2 II. tt:tt IS.'12S :10.1111 :1.4:10'71 420 100 .. 11 .• I .10 '71.1 12.4 41.0 2t.o 14.2 14.1 IO.:S:IIt 1'7.100 :1'7. 1112 :Z.I:ZSSI 421 tO 2 11.1 I .10 '71.5 lt.l JO. I 21.1 ... ., II. I 11.1'712 II. SIO 31.'7SIA :1.10440 420 120 I '1.4 o.ot 10.:1 1'7.1 '7:1.0 23.1 II.S 14.1 1'7.110:1 '72.1SO 41.:1'1:AI :1.11111 421 10 4 1.0 0.01 11.:1 lt.l SO. I 24.1 t0.2 u.s 1'7.1411 II. 1'71 :11.:1114 :t.ll<la4 4:12 t10 4 t0.4 2.20 It. I 17.'1 •••• 2,.. 2 11.3 11.1 It. 11'71 u.:s.,s :11.1111 :r.ISIIO 422 t:SO ., 10.:1 0.20 14.1 14.1 lt.l :so.o 12. I 11.4 14 .144A '10.T'71 <l2.1144 :1.'7101:1 4:14 t2t I I.T I .20 11.2 .... :1 ••. 2 II. 2 11.2 •••• l't.4t'7T II. 100 :t:S.1t41 :t.lt'l't2 421 t31 I 21.1 :1.10 11.1 11.2 1'7.1 11.1 12.:1 11.2 '7:Z.I•c:a '72.1'71 '7'1.1410 4.:11211 421 t:SI I 10.4 0.20 1'7.1 t:r.:s 12.0 II .I IS.o tl, I 1:1.4111 lt.4'7S 21.511'7 :I. :11121 43'1 110 • 12. I 0.00 11.'1 14. 1 12. 1 11. I lt.:r 11.2 '71. 1142 '1'1.421 '71. lf.ol2 4.:1:1211
··················-···························· TttUCX•4 SI'TUII' ... TltUCkwt(aASI:LINII •••••••••o••••••••••o••••••o•••••••••~e••~•••••
RUN A A I' A WfNOOIIt WtiiOSII'O ll'l'ltC1 ll'lltC2 II'CitC2 IOIRCI ll'l!ltC:I II'I'RCI II'CitC'7 ll'lltC& II'GI'OII'fl AIIIITNI_I Yl L.llt.U\.14
441 140 10 1.1 O.Ot 1::1.1 14.1 42.0 I I. I II. I It. '1 41.1222 10.225 2'7. I'• t1 :J.:l11'ft .... , 1:15 I :z.s 0.01 11.2 11.0 41.'7 10.S 10.:1 1'7.0 41. 2'714 10. ,.,. 21. toss :1.01174 441 121 10 I.T 0.10 14.1 14.7 t:Z. 3 0.4 12.1 .... t<l.0421 4'7 TIO 1.%1 II 0 TillS 441 1:15 T S.T O.Ot IA.T 11.0 4::1.1 II. I I'. 7 II. I 41.411:1 11.1'11 21. 1542 :1.2:'1'771 410 140 ., ,,., o.ot '7t.:t 14. t 12.1 17.1 10. I It. 2 II .0420 10. 4'71 :10. S I 21 :1.41111 411 tSO 4 1.4 0.01 t2.2 1'7.1 Sl.2 I I. 1 10.2 11.4 S2.:SI21 II 125 22 . .,12 :Z.411T2 412 ISO I I. I O.Ot 11 '0 tt.:: S2.0 II. S 11.:1 IS s l:t.111T 1:1.321 :ll 14,4 :1.4101:1 4S:J 110 10 2.T O.Ot 11.4 1'7.1 :14.1 T. I II 4 11.1 :II .31 11 Sl 121 IS. l'f:'IS 2 75 liT 4'70 121 • 11 I 2.00 1 ... 2 II. I 10.2 0.5 14.0 11.4 I 4 T'l'll 11.025 2. 2SI:t 0.11412 4Tt 121 14 22. t 1.40 11.4 II. I 24.T 10. I 11.5 It. I 211.10:12 II 100 1 I 1141 2.'7111'7 4T2 t:tl 10 1.1 0.01 II. 1 1'7.1 21.T 1.0 II. I lt.S :11.01'71 11.225 ':z' 1225 2.S'74:J:t 47:1 140 a t<l.:l I .00
'' .t .... 4S.T 10.& 10.2 II s 4:1.1244 17.010 4:1.1241 :J.T'fll:t
4T4 I :'IS I ,.,. I :z.so I., I tt I IS s II. I '15.4 11. I 4t.lt'7'7 51.021 21.1120 :1.:11112 4'7S I :IS I 1.1 I TO 11.:1 1'7.'7 :II. 1 1.1 II.S 11.4 4 I. 0111 10. 1'75 ,.., 124S 2.S40S1 471 I 12 I 12.0 O.Ot 12.'1 11.:1 40. I 14.1 12.4 tl.l 41.1'741 11.01!1 24 4431 :r' 111:1'7 .. .,., 110 12 1:1 ... I. TO 10.1 tl.:t II. I II. I '71.1 t:Z.S 52.1141 I I. 125 12.1141 :1.11241
A-8
!'HAS I! II TltUCK SI'I.ASH STUOY LISTING 01' OATA I'Oit STUOY c:
···············-··-·····-~················ TllUC:ICal SITU!' 01' TllUCK•2{NHTSA(•Yilll .....•...•.................................... It UN AAI!A WtNOOllt WINOSII'D fll!lltC:1 "lltC2 fll!ltC:I l'llltC• fll!ltCI I'IIIICI l'l!ltC"/ "lllCI llGI!OII"/1 AltlTHIS_I .,. I.NitULI6
414 I uo • 2.40 0.01 lt.O 11.:1 4'7.6 26.'7 11.2 lt.o 1"/.1311 11.1'71 :U.2tl'7 :1.1:12'71 411 I tSO I 0.01 0.01 14. 1 ".I 61.:1 3'1.'7 15.'7 11.2 12.11S"P 1"7.221 •:s. 1111 :I."PI3'7S 411 1 131 I 0.01 0.01 12.5 11.0 5o.l 21.'7 11.1 13.0 IS. I "POl 10.225 :11.1010 3.1<10C2 41'7 2 tiO , 1.10 0.01 11.:1 11.0 1'1.0 21.7 10.1 13.2 11.2020 1<1.<150 :U.0111 :1.11311 411 2 110 I 3,10 0.01 '71.1 ••. 1 11.5 21.1 11.1 11.3 57.<1111 16.025 37.1510 :1.11411 411 I 130 I II. 1 11.1 10.1 11.1 11.0 11.1 ..... .,. 17.200 31.1413 3.431"71 410 I 140 I 2.40 0,01 11.1 11.2 so.3 25.1 11.0 14.7 17.1111 11.400 31.&&•:1 3.11030 411 I 1:11 10 1.20 0.01 12.1 11.1 11.4 27. 1 11.1 II. 1 10.3014 11.100 31.74'71 3.15'706 u:l I 110 I 1.20 0,01 11.1 lt.o 14.1 :u.1 11.1 11.1 • ., . 1111 111.110 3$.1122 3.1121"7 412 • 131 I '7.20 o.ao 11.1 12.? 45.0 24.2 11.0 12.3 14.2221 II. 1'75 33.0000 3.41111
••• I 131 I 4.'70 0.01 14.4 11.2 . .. ., 30.4 13.1 11.2 12.1110 .... so 40.711• 3. 70111 411 • 110 I 7.40 0.10 10.1 11.1 31.1 11. I 11.0 11.4 41.1141 17.100 24.1121 3.20327 411 I 110 I '7.10 0.01 10.& 11.1 12.1 21.1 II. 1 12.1 11.2411 a5.ooo 31.5125 3.1'7111 .. , 1 110 4 1.20 0.01 1$,0 13. I 11.0 21.1 13.3 11.1 II .1112 11.4'75 31.4143 :1.1.1'7:1 .... 1 131 • 0.01 0.01 12.3 11.2 1:1.1 21.2 11.1 &1.1 11.24&1 11.110 3&.2131 3.14421 411 2 110 I 0.01 0.01 11.4 1&.4 14.4 23.0 It. I 14.4 11.'7112 n.3so 35.:1123 3.51113
······-······--···············-················ TltUCKtl SITU~ 01' TIIIUCICa1(1ASII.IMI) ···········································-~·-
It UN A It lA WIMOOIR WIMOSPO fllltC1 ~lltC2 fllltC3 fii111C4 fllltCI "llltCI fllltC'7 "llltCI "GIDII11 AJtlTHs_l Y4 LNitULII
••• 1 t:ll 4 11.10 0.01 43.1 11.3 20.2 1'7 •• 34.$ 13.1 31.1021 31.000 11.1121 2.14244 411 1 100 1 1:1.&0 0.10 '72.5 ••. 1 '1.1 3.4 1S.1 12.1 20.124S 44.100 5.0133 1. 12511 411 I 135 I 20.10 '7.'70 41.1 12. 1 41.0 11.2 31.1 IS. 1 31. 1111 41.050 2'7.2114 3.30613 411 2 110 1 4.70 0.01 31.& 12.1 SI.O :Z2.' 2S.I 11.4 40.2t31 41.125 31.353& 3.59330 410 I 110 a 3.SO 0.01 21.0 13.& 41.& 21.1 30.2 IS. 1 42. 1211 47.725 3S.&o647 3.57911 111 ., 110 10 24.10 0.01 7.1 22.1 17.4 IS. 1 10.S 40.3 24.1011 30.125 24.1011 3.20312 412 2 110 I 0.01 0.01 13.1 111.1 2t.2 3.3 11.4 II . ., 24.4010 4:1.110 1.3142 2. t 2311 413 2 110 I 1.20 o.oo 21.S 14.3 31.1 23.0 21.1 It. 1 31.3513 4S.I'7S 30.2131 3.41014 414 2 110 s 12.20 0.20 44.1 12.2 32.5 11.2 14.2 II.S 31. 1434 41. 100 It. 0711 2 ••••• 611 • 110 I s.oo 0.01 13.4 11.4 21.1 1.$ II. 1 11.0 34.4204 10.300 1 •.•• 5. 2.1&415 411 I 110 • 11.10 0.01 14.1 11.3 44.T :n . .,. 34.4 11.2 41.1100 54.000 4 I. 051 t 3.71412 411 I 1<10 I s.1o 1.20 '71.1 11.1 2S.I 11.1 21 .• IS. 1 30.12'71 31.1SO 21. 1'711 3.01551 411 I 131 I 1.10 o.oo 13. 1 11.0 11.0 I. t 11.4 II. 1 :n .1141 12.110 I 1.1133 2 .• 5116 411 1 100 I 1.'70 3.10 11.0 13.1 IS.I 2.3 13.1 II.S 23.3313 10.015 5.1100 I. 71001 soo I 1:1S • a.IO 0.01 t:r.s 11.1 12.1 • •• 14.:1 11.1 30.0143 13.421 1.:1211 2.2:1311 SOl 2 140 I 1.10 1.40 11.0 12.'7 11.s 2.a 1'7.2 II.S 21.0122 41.2$0 .,. . tS12 1.91370
······--··············-··-··-·······-············ TltUCICat SITUI' 01' TltUCktS(I'ULL) ····························-·-·······-······-··· AUN A It lA WI MOO lit WINOS PO "llltCt fllltC2 flllltC:I ltl!ltC4 "IRCI ltlltCI lllltC1 l'l!ltCI llGCOII1& ARITHS_I Y4 LNRU1.14
411 1 110 • 22.1 3.10 42.4 10.1 11.1 1'7.1 32.4 '71.3 11.1121 12.125 11.1121 4.01.71 4'71 1 131 I 1'7.3 0.10 :14.1 11.4 11.1 42.2 41.2 11.1 10.1414 13.125 51.1203 4. o:u 10 410 • ISO I 3.1 0.01 10.3 11.3 2'7.1 4.1 ., . i tS.S 32.3:121 13.110 II. &tO I 2.4:1<1$0 411 1 13S I S. I 0.01 11.4 11.1 SS.I 31. I II.& 11.2 12.1120 II.ISO &2.22&1 3.7&30!1 412 I 110 I 3.5 0.01 12. I 11.4 1S.S 43.0 32.& 1:1.3 52.1511 II. ISO 51.1'711 4.0421'7 &13 I 131 I 3.7 0.01 14.& 11.3 14.0 t2.0 14.7 11.0 34. 1&14 St. &"PS 12.1115 2.1111& 414 1 13S 1 1.$ 0.10 11.0 11.1 II. I I. I !II. I 100. I 34.3313 11.&00 12.0200 2.4&157
••• I 100 10 1.1 0.01 13. 1 11.0 13.1 32.1 13.1 IS. 1 SI.I11C 11.200 61.7712 3.'73233 S02 I 135 • t .1 0.01 10.0 14.3 24.2 11.2 •••• ... .,. 31.1111 51. 171 11. &133 2 .ao 113
fiHASE II TIIIUCIC SPLASH STUDY LJSTUIG 01' OATA ,.a,_ STUDY c
········--·-····-····················-··········· TltUCX•I SETU" 01' TIIIUCk•I(,.UI.I.I ················-···········-······--··--·-····--Ill UN A It lA WlNOOtlt WIMOSPO "lltC1 "IJlC2 "IAC3 fii!JtC4 fllltCS fltrJlCI flt!lt-C'7 lti!JlCI "GI!OSI'71 ARITHS_& v• LNRU1.1!4
503 • 1:11 10 '7.1 0.01 11.1 IS.I 13.3 2.2 1&.1 II. t 23. 1111 53.2'75 5.&013 1.11111 so• I 13S 10 3. I o.o1 11.1 14.1 41.3 25.1 ••. 2 13.& St.ISOI S"P.42S 34. Ill& 3.531&4 sos t 100 I 3.4 0.30 •••• 12.2 ... 11.4 1&.1 lt.O 32.3231 14.'725 10.5111 2.35100 SOl • 110 If It. I 1.10 IC. 1 14.4 32.1 21.1 12.1 11.1 S3. 3111 12.100 21.1031 3.3112& 101 I 131 10 2.3 0.01 1'7.4 11.1 31.1 10.1 ... 1 11.5 41. 1131 • .,. . 111 ".Sill 2.12011 SOl s 110 to 20.2 1.10 Sl. 1 14.1 33.3 ta •• 10.3 11.1 45.3114 54.4"7'5 24.120& :r. 21111 SOl I 120 14 1.2 4.50 11.3 11.7 S.l 3.5 11.1 11.3 21. 1412 II. 125 4.5051 1. 5053 t
A-9
APPENDIX B
TEST VEHICLE DATA
Ma
Mo
v Da
Ty
Cf' WB ........
TRACTOR
ke IU
del XL Series C09670
N IHSRDJWR2EUB24314
te of Mfg. 6-25-84
pe COE, 6X4
420
-
H
Ho
v D
T
s
TRAILER
ke HOBBS
del Ranger Ill
N BLT 9834-02
te of Mfg. 1-80
pe VAN
ze
PHASE II TEST VEHICLE DATA: VEHICI.E COMBINATION A-1, B-1: COE + VAN
.. Hake
Left Goodyear Steer Axle:
Rtaht II
Left OUtside Goodyear Left Inside ..
Front Drive: Right Outside II
Right Inside II
Left Outside Goodyear
Left Inside II
Rear Dri~e: Right Outside II
Right Inside II
Left OuttJI.de Bridges tone Left Inside "
Front Axle: Right Outside Goodyear
Right Inside II
Left Outside To yo
Left Inside Goodyear Rear Axle:
Right Outside It
Right Inside II
----------- .. ·---··---·-·--· -------------'1'1 RE DATA
Type Hfu. No/ID ...
Low Profile Radial Gl59 .. It
Low Profile Radial G167 II II
II II
" II
- ·---Low Profile Radial G167
" .. II " II II
V Steel Radial RIB290 II II
Unisteel Radial -II -- -
Unisteel Radial -It -II -
Slze
285/75 R24.5 .. 285/75 R24.5
It
" .. 285/7 5 R24. 5
II
.. II
11R24. 5 II
II
II
llR24.5
"
II
II
Tread Depth
-
-
11/32
11/32
19/32
19/32
18/32
18/32
17/32
18/32
18/32
18/32
11/32
8/32
11/32
13/32
7/32
. 10/32
8/32
8/32
PHASE II TEST VEHICLE DATA: VEHICLE COHBINATION A-2: SNC + VAN
--. -l'IRE DATA
Hake Type Hrft. No/JD Size Tread Depth ~ --
Left General Steel Radial Amert·:LPR 285/75 124.5 11/32 Hake IH Steer Axle: Rtaht •• .. .. .. 12ll2 Hodel F2375
VIN IUSZEHUR4EHA57014 Left Outside General Steel Radial Aller! LPR 285/75 R24.5 9/32 Left lnatde •• .. .. .. 9/32 Date of Mfg. 6-9-84 Front Drive:
Type SNC 1 6X4 light Outslde .. .. •• .. 10/32 WB 148 light Inslde .. .. .. .. 11/32
· Left Outside General Steel Radial Aaeri LPR 285/75 R24.5 7/32 Left Inside .. .. II .. 9/)2
Rear Drbe: light Outside .. .. .. .. 9/32 light Inside .. .. .. .. 9/32
Le.ft Outatde Brid&eatone V Steel Radial 118290 11R24.5 11/32 ~
Left Inside .. .. II .. 8/32 Hake HOBBS Front Axle: Hodel Ranger III Right Outside Goodyear Uniateel Radial - .. 11/32
Rlaht Inside .. .. - .. 13/32 VIN BLT 98 34-.02
Date of Mfg. 1-80 Left Out:sl<lft T-.,·yo Radial - 11R24.5 7/32 Type ~AU Left Inside Goodyear Unisteel Radial - .. 10/32 Size 96" X 45' Rear Axle:
Right Outside .. .. - .. 8/12 Right Inside .. II - .. 8/32
Ma
Mo
VI
Oa
Ty
OJ WB I w
Ha
Ho
VI
Da
Ty
Si
TRACTOR
ke IH
del F9370 1:-4 2USFBJYR6FCA12954
te of Mfg. 1-31-85
pe LNC, 6X4
560
TRAILER
ke HOBBS
del Ran~er III
N BL1' 9834-02
te of Mfg. 1-80
pe VAN
ze
PHASE II TEST VEHICLE DATA: VEiliCLE COMBINATION A-3: LNC + VAN _________ ..... ------------------1'1 Rt-: DA1'A
Hake Type Hfn. No/ID Slze . ----··----------
Left Goodyear Unisteel Radial Gl59 UR24.5 Steer Axle: II
Right II " tl
----Left Outside Goodyear
I Unisteel Radial Gl67 11R24.5
Left Inside II " .. u
Front Drive: ~
Right Outside .. II It II
Right Inside " II " " ··-·····---
Left Outside Goodyear Unisteel Radial Gl67 11R24.5
Left Inside II " " II
Rear Drive: Right Outside " II .. II
Right Inside II II " II
--
Left Outside Bridges tone V Steel Radial RIB290 11R24.5
Left Inside It II " II
Front Axle: Right Outside Goodyear Unisteel Radial - " Right Inside II tl - ..
-Left Outside 'foyo Radial - 11R24.5
Left Inside Goodyear U11isteel Radial - " Rear Axle:
Right Outside II II - II
Right Inside II II - II
TrE-ad Depth
17/32 17/32
21/32
21/32
21/32
21/32 -----
21/32
21/32
21/32
21/32
11/32
8/32
11/32
13/32
--
---·---------- -·. 7/32
10/32
8/32
8/32
OJ I ~
·---------
TRACTOR
Hake Ill
Hodel F9370
VIH 2USJ.'BJYR6FCA12954
Date of Mfg. 1-31-85
Type LNC 6X4
WB 560
-
TRAILER
Hake Ul;;JL
Hodel
VIN Ill! A ]A 1 6 ~£lll52lllli
Date of Mfg. 2-85
Type 1'ANKEK
Size 9200 Gallun
PHASE II TEST VEHICLE DATA: VEHICI.E COMBINATION C-1: LNC + TANKER
Left Steer Axle:
ataht
Left Outside
Left Jnalde Front Dr tve:
Rlaht Outside
Rtaht Inside
Left Outside
Left Inside Rear Drive:
Rtaht Outside
Rlsbt Inside
Left Outfljde
Left Inside Front Axle:
Rtgbt Outside
Rlaht Inside
l.eft Outside
l .• eft Inside Rear Axle:
Right Outside
Rtsht Inside
I
Hake
Goodyear .. Goodyear
.. II
II
Goodyear .. .. ..
Michelin .. .. II
--------------- .. ·····-·-- ... - ---·-··--- -· 'I'IRE OA1'A
Type Hrn. Nn/10 Size ----·--- ------------
Unisteel Radial Gl59 11R24 .5 II .. ••
·- -
Untateel Radial G167 11R24. 5 .. II II
II .. II
.. u II
-----·· ·-- ...
Unisteel Radial Gl67 UR24.5 .. It II
.. II
II II II
Radial Pilot X2A-1 2 75/80 R24.5 II II II
II II II
.. II ..
'l'n.•ad Dea•t h
17/12
17/32
21/12
21/32
21/32
21/32
21/12
21/32
21/32
21/32
18/12
18/32
18/12
18/32
- Hichel~-"Radtal Pilot X2A-l --------------- ---·---- ------ .... ·- .
2 75/80 R24.5 18/32
18/32 II II
.. ..
.. II
.. II
..
.. 18/]2
18/12
co I
(J1
TRACTOR
Hake IH
Hodel F2375
YIN lHSZEHUR4EHA5 7014
Date of Mfg. 6-9-84
type SNCI 6X4
'-18 148
TRAILER
1ak.e HOBBS
!to del lOOK-48-102
UN 1H5P04821FN017410
!late of Mfg. 12-84
fype FLAIBED . Size
PHASE II TEST VEHICLE DATA: VEHICLE C<»tBINATJON
·'
Hake Type )
Left General Steel Radial Steer Axle: Right .. ..
Left Outside General St~el Radial Left Inside .. ..
Front Drive: Right Outside .. .. Rtaht Inside .. ..
· Left Outside General Steel Radial Left lndde ..
Rear brfye: Right Outside .. Right lnaide ..
Left Outside Goodyear Left Inside ..
Front Axle: Right Outslde .. Right Inside .. Left Outside Goodyear Leh Inside ..
Rear Axle: Right Outside It
Right Inside ..
C-2 SHC + FLATBED
-. 1'1RE DATA Hfa. No/ID Size Tread Depth
Ameri LRR 285/75 R24.5 11/32 .. .. 12LJ~
Ameri LPR 285/75 R24.5 9/32 •• •• 9/32 .. .. 10/32 .. .. 11/32
Ameri LPR 285/75 R24.5 7/32 .. .. 9/32
.. .. 9/32 .. .. 9/32
-
Hi-Hiler CS 11-24.5 15/32 .. .. 15/32
.. .. 15/32 .. .. 15/32
lli-MUer CS 11-24.5 15/32 .. .. 15/32
.. II 15/32 II II 15/32
o:r-1
0"1
TRACTOR Hake t:OBJl Hodel CL9000
VIM 1FDXZ96R8CVA51419
Date of Mfg.
Type SNC 4X2
WB 120
lat TRAILER
Hake FRUEUOF
Hodel FB9-F240
VIM HES 4049-39
DOLLY
2nd TRAILER
Hake~
PIIASI II TEST VIHICLI DATA: VEHICLE C()HIJNATION
·'
Hake
Left Goodyear Steer Axle:
ataht ••
Left Outalde Goodyear
Left lnalde .. Front Dr lve:
ataht Outalde .. Rlaht lnatde ••
· Left Outside Goodyear
Left lnalde •• Rear Drhte:
Rtaht Outalde Kelly
Rtaht lnatde BP Goodrich
. .,.
Left Out11lde BP Goodrich Left Jnalde ..
Front Axle: Rtaht Outaide Kelly Rlaht Inside •• Left Outside Goodyear Left Inside ..
Rear Axle: Riaht Outside BF Goodrich Right Inside It
C-l: COl + -~__!!!:~-!~-=------.. 1'1RI DATA
Type Hfn. No/ID Slo:e Tread Depth -
Radial Gl59 285/75 124.5 17/12 .. .. 17/12
Radial Gl67 11R24.5 12/32 .. .. .. 10/32
.. .. .. 12/32 .. .. .. 12/32
CFL lO.OQ-20 7/12 •• .. 6/32
Pneatwa liB .. 11/32
Traction Expreea .. 10/l2
Xtra Miler Preatua lO.OQ-20 11/12 .. .. 9/32
Ddve Track .. 9/32 II tl 9/32
Custom Cross RIB 10.00-20 11/32 II .. 10/12
Front Wheeler .. 17/32
IJeavy Duty Express It 10/12
APPENDIX C
EQUIPMENT INSTALLATION INSTRUCTIONS AND INSTALLED MEASUREMENTS
TTl INSTRUCTIONS
MOUNTING OF SPLASH AND SPRAY DEVICES FOR PHASE II TESTING
As was the case in the earlier splash and spray testing, flaps and
skirts should be installed according to the manufacturers' gu1delines
and recommendations. In addition, the mounting of flaps and skirts for
Phase II should be consistent with the newly proposed NHTSA
requirements.
The proposed NHTSA mounting requirements are outlined below.
Flap Location
o Flaps should be at least 2 inches, but not more than 12 inches
behind the tire.
o If the tire is on a sliding axle assembly, the flap should
move with the axle so that the 2-12 inch range is maintained.
Flap Height, Upper Edge
o The upper edge should be at least as high as the top of the
tire.
o If this is not possible, then the flap should be moun~ed so
that the upper edge is no lower than the bottom of the frame
rai 1 •
C-1
o If there is a fender behind the wheel that is from 2-12 inches
behind the tire, then the upper edge of the flap should be
attached to the fender such that there is no more.than a 1 inch
gap between the flap and the fender. This gap should be
sea 1 ed.
Flap Height, Lower Edge
o On the steering axle, the flap should be mounted so that the
lower edge of the flap is no higher than a 10 degree angle
between the ground and a plane tangent to the vertical
centerline of the wheel.
o On other axles, the angle E should not be greater than
15 degrees.
Flap Width
o Flaps should be mounted so that they cover the entire width
of the tire(s).
Skirt Location
o Skirts should be mounted so that they cover at least the
entire distance from the front to the rear of the tire(s)
they are protecting.
o On the nose of semitrailers, skirts should be mounted so that
the forward edge is even with the most forward point on th.e
side of the semitrailer and should extend at least 8 feet.
o There shou 1 d be no mor.e than a 1 inch gap between the skirt
and trailer.
C-2
Skirt Height
o Skirts should hang down from the vehicle at least to the level
of the top of the tires.
o Vertical height of skirts should be no less than 6 inches.
C-3
Tmcll T~tor. Trailer. Of
u>nvttrlOf OoUv ftaaa.te Rail
I ~
.;8
c. - o.c• flap
A = Horizontal distance from rear-most point on tire to flap n B = Vertical distance from top-most point on tire up (+) or L down (-) to upper edge of flap
C = Vertical distance from bottom of frame rail up (+) or down (-) to upper edge of flap
0 = Angle between a plane tangent to the vertical ~enter line of the wheel and the lower edge of flap, and the ground
E = Vertica.l distance from lowest point of tire to lower edge of flap
F = Flap width overlap of tire sidewalls G = Vertical overhang of skirt below tire top H = Hori zonta 1 overlap of skirt, fore I = Horizontal overlap of skirt, aft
1-f
& liii~--~ ... :.:.:SZ .. ,
1• Sldewal to Sidawal , ... f--.-- •••• c.
Figure C-1. Flaps and skirt installed measurements (See Table C-1)
VEHICLE COMBINATION A-1, B-1 TABlE C-1 Flap and Skirt Installed Measurements TRACTOR COE 6x4 --TRAilER VAN DIMENSION (See Fig. C-1)
A B c D E F G H I .
left Inboard 3.00 - 0.75 - 4.25 -1.00 STEER Outboard 3.00 - - <10° 4.50 2.75 4.25
AXLE Right Inboard 2.25 - 0.75 - 4.25 -0.50 Outboard 2.25 - - <10° 4.25 2.50 2.50
left Inboard 5.25 -0.75 9.-75 - 4.50 -1.00 DRIVE Outboard 4.25 0.75 11.00 <15° 5.00 1.00 4.50 0.75 4.00
AXLE Right Inboard 2.50 1.00 11.75 - 4.75 -0.50 Outboard 3.25 1.25 12.00 <15° 6.25 0.25 4.25 1.75 2.25
left Inboard 2.25 4.00* - - 4.50 1.25 TRAILER Outboard 2.25 4.00* - <15° 4.00 -1.25 5.50 2.50 1.00
AXLE Right Inboard 2.25 3.75* - - 4.75 1.25 Outboard 1. 75 3.00* - <15° 5.00 -1.25 5.50 3.00 0.00 n
I U1
*To top of insert
VEJHCLE COMBINATION A-2 TABlE C-1 flap and Skirt Installed Measurements TRACTOR SNC 6x4 --TRAILER VAN DIMENSION (See Fig. C-1) --
A B c D E F G H I
left Inboard 6.00 - 6.00 - 3.75 1.00 Outboard 7.00 - - <10° 4.50 1.25 0.75 STEER
AXLE Right I.1board 6.50 - 6.50 - 4.00 1.00 Outboard 7.00 - - <10° 4.25 1.25 0.00
left Inboard 4.00 - - - 5.50 0.00 Outboard 4.50 - - <15° 5.50 0.00 2.50 0.50 3.00 DRIVE
AXLE Right Inboard 4.00 - - - 6.25 0.00 Outboard 5.00 - - <15° 6.00 0.25 0.75 0.00 0.00
left Inboard 2425 4.00* - - 4.50 0.12 TRAILER Outboard 2.25 4.00* - <15° 4.00 -0.12 5.5(J 2.50 1.00
AXLE Inboard 2.25 3.75* - - 4.75 0.12 n Right Outboard 1. 75 3.00* - <15°· 5.00 -0.12 5.50 3.00 0.00 I 0)
~-,--. ~ -·-- ----·· -·-- ..
*To top of insert
VEHICLE COMBINATION A-3 TABLE C-1 Flap and Skirt Installed Measurements TRACTOR LNC, 6x4 TRAILER VAN DIMENSION (See Fig. C-1)
A B c D E F G H I
left Inboard . 7.00 - 3.50 - 4.25 7.50 STEER Outboard 6.25 - - <10° 3.75 1.25 3.00
AXLE Right Inboard 5.75 - 3.50 - 4.00 7.25 Outboard 5.75 - - <10° 4.00 1.25 3.00
left Inboard 3.50 -1.00 - - 6.50 0.00 DRIVE Outboard 4.00 -1.00 - <15° 6.50 0.00 4.25 1.75 -1.50
AXLE Right Inboard 2.50 -1.00 - - 6.50 0.00 Outboard 3.25 -1.50 - <15° 6.00 0.00 3.75 2.75 -1.50
left Inboard 2.25 4.00* - - 4.50 0.12
TRAILER Outboard 2.25 4.00* - <15° 4.00 -0.12 5.50 2.50 1.00
AXLE Right Inboard 2.25 3.75* - - 4.75 0.12 n Outboard 1. 75 3.00* <15° 5.00 -0.12 5.50 3.00 0.00 I -.......
*To top of insert
VEHICLE COMBINATION C-1 TABLE C-1 Flap and Skirt Installed Measurements TRACTOR lNC, 6x4
TRAilER TANK DIMENSION (See Fig. C-1) --A 8 c D E F G H I
left Inboard 7.00 - 3.50 - 4.25 7.50 Outboard 6.25 - - <10° 3.75 0.12 3.00
STEER AXLE Right Inboard 5. 75 - 3.50 - 4.00 7.25
Outboard 5.75 - - <10° 4.00 -0.12 3.00
left Inboard 3.50 -1.00 - - 6.50 0.00
DRIVE Outboard 4.00 -1 00 <15° 6.50 0.00 1.00 5.50 -2.00
AXLE Right Inboard 2.50 -1.00 - - 6o50 0.00 Outboard 3.25 -1.50 - <15° 6.00 0.00 2.00 4.75 -2.75
left Inboard 2.50 -6.00* - - 7.50 Outboard 2.00 -6.00* - <15° 7.50 - 3.25 4.75 2.00
TRAilER AXlE Right Inboard 2.50 -6.00* - - 7 .. 00
Outboard 2.75 -6.00* - <15° 7.25 - 3.50 2.00 2.00 ("')
8 CX>
* Fender structure fills to above top of tire
VEHIClE COMBINATION C-2 TABLE C-1 Flap and Skirt Installed Measurements TRACTOR SNC, 6x4
TRAILER FLATBED DIMENSION (See Fig. C-1) --A 8 c D E F G H I
left Inboard 8.00 - 6.00 - 4.50 STEER Outboard 8.50 - - <10° 4.75 - 0.75
AXLE Inboard 6.50 - 6.50 - 4.25 Right Outboard 7.00 - - <10° 4.75 - 0.00
Left Inboard 4.00 0.50 - - 5.50 0.00 DRIVE Outboard 4.25 0.50 - <15° 5.50 0.00 1.25 0.00 3.25
AXLE Inboard 3.75 0.25 - - 6.25 0.00 Right Outboard 4.25 0.25 - <15° 5.75 0.25 0.75 0.50 2.50
left Inboard 3.00 -7.00* - - 6.50 -0.25 TRAILER Outboard 2.00 -7.00* - <15° 6.50 -0.25 3.00 1.25 2.00
AXLE Inboard 2.75 -7.00* - - 6.25 -0.75 Right Outboard 3.00 -7.00* - <15° 6.75 0.00 3.00 1.00 2.25 -.
("') I
lO
*Fender structure fills to top of tires
VEHICLE COMBINATION C-3 TABLE C-1 flap and Skirt Installed Measurements TRACTOR COE, 4x2 TRAILER DOUBLE VAN DIMENSION (See Fig. C-1) --
A 8 c 0 E F G H I
left Inboard 4.50 -6.50 5.75 5.00 -0.50 Outboard - 1.00 5.00 STEER
AXLE Right Inboard 4.50 -9.00 7.00 5.00 0.50
Outboard - 1.00 5.50
left Inboard 11.00 2.00 15.00 8.50 -0.50 Outboard - 0.50 6.00 2.00 3.50 DRIVE
AXLE Right Inboard 10.00 2.00 14.00 8.00 0.50
Outboard - 0.00 5.00 3.50 1.00
;_eft Inboard 4.00 -1.00 5.0U 8.75 0.25 Outboard - -0.50 4.5(1 ~.~0 4.50 1st TRAILER
AXLE Right Inboard 3.75 -2a00 5.00 8.50 0.00
Outboard - -0.50 5.00 3.50 3.50 n I
....... 0
Inboard 3.00 1.00 9.00 5.25 0.00 left - 0.00 2.00 2.50 4.50 Outboard DOllY
Inboard 0.00 Right 4.00 1.00 11.50 - 6.25 0.00 1.00 2.50 4.00 Outboard
Inboard 6.00 -4.50 2.00 6.75 0.25 left - 0.00 4.50 3.50 4.00 Outboard 2nd TRAILER
Inboard 6.00 -4.50 2.00 - 7.50 0.00 Right Outboard 0.00 3.50 3.50 3.50